{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "8fee91a2-2121-44ef-81b3-11ffc68db20d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I read in the Census tract data\n"
     ]
    }
   ],
   "source": [
    "#THIS snaps vtd-based Ohio congressional for Akron-Cin-Cle-Day-Toledo  #from muniSnap15 1/11/25\n",
    "#this version mostly duplicated from OH_schoolSnap15, but using muniSnap99's generation of units\n",
    "from shapely.geometry import Point, LineString, Polygon, box\n",
    "import shapely\n",
    "import geopandas as gpd\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import ast\n",
    "import time\n",
    "from numpy import random\n",
    "from scipy.stats import norm\n",
    "import math\n",
    "tractPopFile = gpd.read_file(\"state_map_files/oh_pl2020_vtd.dbf\")  # ***USING VTDs ***\n",
    "tractPopFile.head()  #about 40 sec to load\n",
    "print(\"I read in the Census tract data\")\n",
    "#handy function for plotting Polygon or multiPolygon tracts and precincts\n",
    "def plotPoly(inputPoly,LW=1):\n",
    "    dummyPoly = Polygon([(0,0),(0,1),(1,1)])\n",
    "    if inputPoly.geom_type == dummyPoly.geom_type:\n",
    "        x,y = inputPoly.exterior.xy\n",
    "        plt.plot(x,y,lw=LW)\n",
    "    else:\n",
    "        for geom in inputPoly.geoms:\n",
    "            if geom.area > 0:  #to avoid error with LineString geom parts\n",
    "                x,y = geom.exterior.xy\n",
    "                plt.plot(x,y,lw=LW)  \n",
    "def plotCenter(t,geom,FONTSIZE=10):\n",
    "    plt.text(geom.centroid.x,geom.centroid.y,t,ha='center',fontsize=FONTSIZE)\n",
    "    \n",
    "def r3(number):\n",
    "    result = round(number,3)\n",
    "    return result\n",
    "\n",
    "def r5(number):\n",
    "    result = round(number,5)\n",
    "    return result\n",
    "\n",
    "def getAdjoiners(UNITLIST, UNITNBRS): #returns all units that neighbor a UNITLIST but are not in the UNITLIST \n",
    "    allNbrs = list()\n",
    "    for U in UNITLIST:\n",
    "        allNbrs = allNbrs + UNITNBRS[U]\n",
    "    adjoiners = list( set(allNbrs).difference(set(UNITLIST)) )\n",
    "    return adjoiners\n",
    "\n",
    "def get2nbrs(ULIST, UNITNBRS):\n",
    "    \"\"\"\n",
    "    Get the combined list of first- and second-level neighbors of a LIST, using neighborList connectivity.  Excludes the source list\n",
    "    \"\"\"\n",
    "    firstList =  getAdjoiners(ULIST, UNITNBRS)\n",
    "    secondList = getAdjoiners(firstList, UNITNBRS)\n",
    "    twoLevelList = list( set(firstList + secondList).difference(set(ULIST) ) )\n",
    "    return twoLevelList\n",
    "\n",
    "def getContigFromStarter(starter, VLIST, NEIGHBORLIST):  #all contiguous units in VLIST, starting from starter unit\n",
    "    foundList, newList, prevList = [ starter ], [ starter ], [ starter ]\n",
    "    while len(newList) > 0:\n",
    "        newList = list()\n",
    "        for V in prevList:\n",
    "            for VV in NEIGHBORLIST[V]:\n",
    "                if VV in VLIST and VV not in foundList:\n",
    "                    newList.append(VV)\n",
    "                    foundList.append(VV)\n",
    "        prevList = newList.copy()        \n",
    "    return foundList   \n",
    "\n",
    "def isContiguous(VLIST,NEIGHBORLIST,returnBiggestPiece=False):\n",
    "    \"\"\"\n",
    "    This method determines if all items in a list form a continuous chain of neighbors based on the passed neighborlist\n",
    "    Empty lists are considered contiguous.  If discontiguous, a less-than-majority piece list is returned,\n",
    "     unless giveBig=True, in which case we return the biggest piece\n",
    "    \"\"\"    \n",
    "    isUnbroken, newList, foundList = True, list(), list()\n",
    "    if len(VLIST) > 0:\n",
    "        foundList, newList, prevList = [ VLIST[0] ], [ VLIST[0] ], [ VLIST[0] ]\n",
    "    while len(newList) > 0:  #this round's list of neighbors\n",
    "        newList = list()\n",
    "        for V in prevList:\n",
    "            for VV in NEIGHBORLIST[V]:\n",
    "                if VV in VLIST and VV not in foundList:\n",
    "                    newList.append(VV)\n",
    "                    foundList.append(VV)\n",
    "        prevList = newList.copy()      \n",
    "    pickedPieceList = foundList.copy()  #default contiguous sublist to pass back to main\n",
    "    \n",
    "    if len(foundList) < len(VLIST):  #not contiguous\n",
    "        isUnbroken  = False\n",
    "        pieceLists, remainingList = [foundList], list( set(VLIST).difference(set(foundList) ) )\n",
    "        if returnBiggestPiece == True:  #we were asked for the biggest piece, not a random small one, so we must find them all\n",
    "            if len(foundList) < 0.5*len(VLIST):\n",
    "                while len(remainingList) > 0:\n",
    "                    newList = getContigFromStarter(remainingList[0], remainingList, NEIGHBORLIST)\n",
    "                    pieceLists.append(newList)\n",
    "                    remainingList = list(set(remainingList).difference(set(newList)))\n",
    "                pieceLengths = [len(pL) for pL in pieceLists]\n",
    "                pickedPieceList = pieceLists[ pieceLengths.index(np.max(pieceLengths)) ]\n",
    "            \n",
    "        else: #quickly return a contiguous sub-list that's at most half the total units in the list\n",
    "            if len(foundList) > 0.5*len(VLIST): #pick a different piece; this one is the majority\n",
    "                pickedPieceList = getContigFromStarter(remainingList[0], remainingList, NEIGHBORLIST)\n",
    "                \n",
    "    return isUnbroken, pickedPieceList\n",
    "\n",
    "def enclaveCheck(UNITLIST,UNITNBRS,maxLoops=2):  #TRY 2 FOR OHIO V2.  USUALLY 4\n",
    "    \"\"\"\n",
    "    This method determines if a list of units has an unbroken boundary AND whether its complement has an unbroken boundary\n",
    "    If the complement boundary is broken, there is an enclave or the district is so disconnected its adjoining units aren't contiguous\n",
    "    The method returns contiguity of boundary and of its adjoiners.  Also returns the lists of boundary and complement-boundary units\n",
    "      If either of these is broken, only a contiguous sublist is returned that is guaranteed to be smaller than half (for finding enclaves)\n",
    "      maxLoops is the number of loops for expanding neighbors-of-neighbors for contiguity of the units outside the passed unit-list\n",
    "    \"\"\"\n",
    "    UNITSET = set(UNITLIST)\n",
    "    ADJLIST =  get2nbrs(UNITLIST, UNITNBRS)  #in case direct adjoiners are only queen-adjacent\n",
    "    #adjoinersOfAdjoiners = getAdjoiners(ADJLIST,  UNITNBRS)\n",
    "    #BDRYLIST = list( set(UNITLIST).intersection(set(adjoinersOfAdjoiners)) )  #this might fail for queen-adjacent boundary units\n",
    "    BDRYLIST = list (set(get2nbrs(ADJLIST,UNITNBRS)).intersection(UNITSET) )  #in case inHD boundary is only queen-adjacent\n",
    "    noEnclave, enclaveList =   isContiguous(ADJLIST, UNITNBRS)  \n",
    "    unbroken, smallPieceList = isContiguous(BDRYLIST, UNITNBRS)\n",
    "    if not unbroken: #could be that district's boundary intersects the state boundary or there is a nonHD enclave inside the HD\n",
    "        unbroken, smallPieceList = isContiguous(UNITLIST, UNITNBRS)  #slower check for full district, not just its boundary \n",
    "    nLoops = 1 #could be that fragmented adjoining districts are underestimating true contiguity.  Widen the contig search\n",
    "    while nLoops <= maxLoops and not noEnclave:\n",
    "        nLoops +=1\n",
    "        newSet = set(ADJLIST)\n",
    "        for UU in ADJLIST:\n",
    "            newSet = newSet.union( set(UNITNBRS[UU]).difference(UNITSET) )\n",
    "        ADJLIST = list(newSet)\n",
    "        noEnclave, enclaveList =   isContiguous(ADJLIST, UNITNBRS)\n",
    "    #isJiggy = noEnclave and unbroken\n",
    "    return unbroken, noEnclave, smallPieceList, enclaveList\n",
    "\n",
    "def getBdryNonEdgers(UNITLIST, UNITNBRS): #all in-district boundary units that neighbor a non-district unit\n",
    "    ALLnonHDnbrs = set()\n",
    "    for UUU in UNITLIST:\n",
    "        ALLnonHDnbrs = ALLnonHDnbrs.union(set(UNITNBRS[UUU])).difference(set(UNITLIST))\n",
    "    BdryNonEdgerSet = set()\n",
    "    for UUU in UNITLIST:\n",
    "        if len(set(UNITNBRS[UUU]).intersection(ALLnonHDnbrs)) > 0:\n",
    "            BdryNonEdgerSet.add(UUU)\n",
    "    return list(BdryNonEdgerSet)\n",
    "\n",
    "def getEnclaveLists(UNITLIST, UNITNBRS):\n",
    "    \"\"\"\n",
    "    finds ALL units enclaved by a UNITLIST, parsed into lists of contiguous pieces\n",
    "    We assume the largest contiguous complement to the UNITLIST is not an enclave, but rather the majority of the HD complement\n",
    "    if the UNITLIST's complement (all couldBeEnclaved) is contiguous, the returned list will be blank\n",
    "    \"\"\"\n",
    "    eSets, nU = list(), len(UNITNBRS)\n",
    "    offmapList = list()\n",
    "    for i,L in enumerate(UNITNBRS):\n",
    "        if len(L) == 0:\n",
    "            offmapList.append(i)  #offmap list are units with no neighbors (were surrounded)\n",
    "    complementSet = set([i for i in range(nU)] ).difference( set(UNITLIST + offmapList) )    \n",
    "    remaining2nbrs = get2nbrs(UNITLIST, UNITNBRS)\n",
    "    \n",
    "    isContig, shortList = isContiguous(remaining2nbrs,UNITNBRS) #quicker than contig check on entire complement\n",
    "    while not isContig:  #this will kick out before writing the final sublist = map majority\n",
    "        starter = shortList[0]\n",
    "        newEnclaveList = getContigFromStarter(starter, list(complementSet), UNITNBRS)\n",
    "        eSets.append(set(newEnclaveList))\n",
    "        remaining2nbrs = list(set(remaining2nbrs).difference(set(shortList)) )\n",
    "        isContig, shortList = isContiguous(remaining2nbrs,UNITNBRS)\n",
    "        \n",
    "        # couldBeEnclaved = list( set(couldBeEnclaved).difference(set(newEnclaveList)) )  #revised 18-Feb-24 -- was slower\n",
    "    fused_eSets = set()\n",
    "    for i, eSet in enumerate(eSets):\n",
    "        fused_eSets = fused_eSets.union(eSet)\n",
    "        for j in range(i+1, len(eSets) ) :\n",
    "            eSets[j] = eSets[j].difference(eSet)  #in case contiguity occurs, but not in 2-neighbor list; avoid double-count\n",
    "    remnant_eSet = complementSet.difference(fused_eSets) \n",
    "    eLengths = [len(eSet) for eSet in eSets]\n",
    "    if len(eSets) > 0:\n",
    "        if len(remnant_eSet) < np.max(eLengths):  #exchange the small remnant for the biggest found \"enclave\" (usually the major complement) \n",
    "            eSets[eLengths.index(np.max(eLengths))] = remnant_eSet.copy()\n",
    "    eLists = [list(eSet) for eSet in eSets]\n",
    "    return eLists\n",
    "\n",
    "def wontEnclave(proposedU, dList, NBRLIST, mapBDRYLIST):  #TRY MAXLOOPS = 3 FOR OH REDO, NOT USUAL 6\n",
    "    \"\"\"\n",
    "    This method checks if adding a proposedU to a dList (list of units in a district) will create an \"enclave\" of units in the dList's complement\n",
    "    via two problems:  A) the dList will now have a discontiguous set of units on the map boundary.  The full map boundary list is mapBDRYLIST\n",
    "      B) The non-dList neighbors of dList units aren't contiguous\n",
    "    The method doesn't require that the dList wontEnclave without the proposedU included; it just checks the proposedU + dList combination\n",
    "    It also doesn't check that the dList is itself contiguous with or without proposedU\n",
    "    In that sense, it is more limited than enclaveCheck\n",
    "    \"\"\"\n",
    "    wontEnclave = True\n",
    "    newList, newSet = dList + [proposedU], set(dList + [proposedU])\n",
    "    unitsOnBoundary = list( set(mapBDRYLIST).intersection(newSet) )\n",
    "    wontEnclave, __ = isContiguous(unitsOnBoundary,NBRLIST)  #first check - does district touch MAP boundary in multiple places? (quick FAIL)\n",
    "    if wontEnclave: #slower check below for internal enclaves\n",
    "        adjoiners = get2nbrs(newList, NBRLIST)  #2-level to protect for queen adjacency in boundary        \n",
    "        wontEnclave, __ = isContiguous(adjoiners,NBRLIST)\n",
    "        if not wontEnclave:\n",
    "            nLoops = 1 #could be that fragmented adjoining districts are underestimating true contiguity.  Widen the contig search\n",
    "            maxLoops, ADJLIST = 3, adjoiners #unlike enclaveCheck, here we just arbitrarily set a number of loops for search expansion\n",
    "            while nLoops <= maxLoops and not wontEnclave:\n",
    "                nLoops +=1\n",
    "                adjSet = set(ADJLIST)  #align nomenclature w enclaveCheck\n",
    "                for UU in ADJLIST:\n",
    "                    adjSet = adjSet.union( set(NBRLIST[UU]).difference(set(newList)) )\n",
    "                ADJLIST = list(adjSet)\n",
    "                wontEnclave, __ =   isContiguous(ADJLIST, NBRLIST)\n",
    "        \n",
    "    return wontEnclave\n",
    "\n",
    "def isRookAdj(geo1, geo2):  #intersection with rook (not queen) adjacency\n",
    "    isRookAdj = False\n",
    "    if geo1.intersects(geo2):\n",
    "        if (geo1.intersection(geo2)).geom_type != Point(0,0).geom_type:\n",
    "            isRookAdj = True\n",
    "    return isRookAdj\n",
    "\n",
    "def getWeightedAvgAndSD(LIST, WEIGHTS):\n",
    "    nWeights = len(WEIGHTS)\n",
    "    normWeights = [WEIGHTS[i] / np.sum(WEIGHTS) for i in range(nWeights) ]\n",
    "    AVG = 0.\n",
    "    for i, value in enumerate(LIST):\n",
    "        AVG += normWeights[i] * value\n",
    "    sumVar = 0.\n",
    "    for i, value in enumerate(LIST):\n",
    "        sumVar += normWeights[i] * (value - AVG)**2\n",
    "    SD = sumVar ** 0.5     #don't need to normalize again since weights were normalized\n",
    "    return AVG, SD\n",
    "\n",
    "def getHDcp(TRACTCP,TRACTPOP, TRACTLIST, SPLITTRACTNO = -777,SPLITTRACTUSE = 1.):  #population centerpoint of a Home District or county (cluster)\n",
    "    cpx, cpy, sumPop = 0.,0., 0.\n",
    "    for tt in TRACTLIST:\n",
    "        USE = 1.\n",
    "        if tt ==    SPLITTRACTNO:\n",
    "            USE =   SPLITTRACTUSE\n",
    "        sumPop += USE*TRACTPOP[tt]\n",
    "        cpx +=    USE*TRACTPOP[tt] * TRACTCP[tt].x\n",
    "        cpy +=    USE*TRACTPOP[tt] * TRACTCP[tt].y\n",
    "    HDCP_ = Point(cpx/sumPop, cpy/sumPop)\n",
    "    return HDCP_\n",
    "\n",
    "dummyPoly = Polygon([(0,0),(0,1),(1,1)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a9e2fbed-247e-4a00-be18-5507b7e2b88f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are 8941 popn tracts for OH\n"
     ]
    }
   ],
   "source": [
    "# EXTRACT TRACT GEOMETRIES AND POPULATIONS INTO LISTS, COMPUTE TRACT AREAS\n",
    "STATE = \"OH\"\n",
    "tractGeom = tractPopFile['geometry']  #for some states, replace with tractGeomFile\n",
    "tractPop = tractPopFile['P0010001']\n",
    "tractVAP = tractPopFile['P0030001']   #NEW 3/2/22 - USE VAP\n",
    "# tractPop2 = tractPopFile['P0020001']   #not needed; confirmed that this matches P00100001 exactly\n",
    "tractHisp = tractPopFile['P0040002']   #NEW 3/2/22 - USE VAP\n",
    "tractBlack = tractPopFile['P0030004']  #NEW 3/2/22 - USE VAP\n",
    "tractCountyNo = tractPopFile['COUNTYFP20']\n",
    "nTracts = len(tractPop)\n",
    "nVTDs = nTracts #nomenclature\n",
    "tractCP = [tractGeom[v].centroid for v in range(nVTDs) ]\n",
    "tractCPx, tractCPy = [tractCP[v].x for v in range(nVTDs)], [tractCP[v].y for v in range(nVTDs)]\n",
    "print(\"there are {0} popn tracts for {1}\".format(nTracts, STATE) )\n",
    "tractArea = [0.]*nTracts\n",
    "tractCountyNo = tractCountyNo.to_numpy()\n",
    "countyNo = [0]*nTracts\n",
    "for t in range (0,nTracts) :  #from odd-numbered counties in US Census list to integer list\n",
    "    tractArea[t] = tractGeom[t].area\n",
    "    countyNo[t] = int((int(tractCountyNo[t]) - 1)/2)\n",
    "isSkippedTract = [0] *nTracts  #this will house a temporary list of tracts for manipulation\n",
    "tractPop = tractPop.to_numpy()  #to avoid panda overwrite grousing\n",
    "tractBlack= tractBlack.to_numpy()\n",
    "tractHisp = tractHisp.to_numpy()\n",
    "tractVAP = tractVAP.to_numpy()\n",
    "stateVAP = np.sum(tractVAP)\n",
    "nCounties = int( np.max(countyNo)+1)\n",
    "skipList = [8197, 4634, 3730, 4458, 840, 2974, 1008]\n",
    "for t in skipList : #coastal vtds for Ohio already known\n",
    "    isSkippedTract[t] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "a619e262-3e70-4945-87b1-58245cc514c4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on tract 0\n",
      "working on tract 1000\n",
      "working on tract 2000\n",
      "working on tract 3000\n",
      "working on tract 4000\n",
      "working on tract 5000\n",
      "working on tract 6000\n",
      "working on tract 7000\n",
      "working on tract 8000\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# CREATE COUNTY-LEVEL MAP OF THIS STATE - excluding lakeshore tracts from county building\n",
    "for s in skipList :\n",
    "    countyNo[s] = -999  #don't count these lakeshore tracts as part of a county\n",
    "dummyPoly = Polygon([ (0,0),(1,0),(1,1)])\n",
    "countyGeom = [dummyPoly]*nCounties\n",
    "lakeErieGeom = []\n",
    "countyPop = [0.]*nCounties\n",
    "nCountyTracts = [0]*nCounties  #how many tracts found in this county\n",
    "countyTractList = [list() for c in range(nCounties) ]\n",
    "for t in range(nTracts):  #now loop through tracts, assign each to county, build county polygons\n",
    "    if t%1000 == 0:\n",
    "        print(\"working on tract\",t)\n",
    "    if t not in skipList:\n",
    "        c = int(countyNo[t])\n",
    "        countyTractList[c].append(t)\n",
    "        nCountyTracts[c] +=1   #found another tract that belongs to this county\n",
    "        countyPop[c] += tractPop[t]\n",
    "        if nCountyTracts[c] == 1:  #this is the first tract found for this county\n",
    "            countyGeom[c] = tractGeom[t]  #seed the county geometry polygon\n",
    "        else:\n",
    "            countyGeom[c] = countyGeom[c].union(tractGeom[t])\n",
    "countyMAP = countyGeom[0]\n",
    "for c in range(nCounties):  #now build the state map from the counties\n",
    "    plotPoly(countyGeom[c])\n",
    "    plotCenter(c,countyGeom[c],8)\n",
    "    countyMAP = countyMAP.union(countyGeom[c])\n",
    "plotPoly(countyMAP)\n",
    "plt.show()   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "0bacf56a-d610-40d7-83a8-fe6ff799a41c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now determine the county topology\n"
     ]
    }
   ],
   "source": [
    "print(\"Now determine the county topology\")\n",
    "countyNeighbors = [list() for c in range(nCounties)]\n",
    "for c in range(nCounties):\n",
    "    for cc in range(c+1, nCounties):\n",
    "        if isRookAdj(countyGeom[c],countyGeom[cc]):\n",
    "            countyNeighbors[c].append(cc)\n",
    "            countyNeighbors[cc].append(c)\n",
    "mainMAP = countyMAP.geoms[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "cda12941-0eef-4a29-a376-dd0d4bc2927b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "15 districts, each with avgDistrictPop of 786629.867\n",
      "I will now build a map from the counties\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#quick block to flag the whole county-districts -- though we do not use any whole-county units in this version\n",
    "MAP = dummyPoly\n",
    "#perfectCounty = [0]*nCounties  #\"perfect\" counties have the perfect population for a whole district\n",
    "#wholeCounty = [0]*nCounties    #\"whole\" counties are either perfect or small enough that they should be kept whole\n",
    "#minCountyRatio = 0.15   #not designated in this code\n",
    "#lockedTract = [0]*nTracts\n",
    "nDistricts = 15 #Congrl\n",
    "statePop = np.sum(tractPop)\n",
    "avgDistrictPop = statePop/nDistricts\n",
    "aDP = avgDistrictPop\n",
    "maxDevn = 0.005\n",
    "print(nDistricts,\"districts, each with avgDistrictPop of\",r3(avgDistrictPop))\n",
    "print(\"I will now build a map from the counties\") # and display the whole county districts\")\n",
    "for c in range(nCounties):\n",
    "    if MAP == dummyPoly:\n",
    "        MAP = countyGeom[c]\n",
    "    else:\n",
    "        MAP = MAP.union(countyGeom[c])\n",
    "    #if countyPop[c] >= (1.-maxDevn)*avgDistrictPop and countyPop[c] <= (1.+maxDevn)*avgDistrictPop :\n",
    "    #    perfectCounty[c] = 1\n",
    "    #    wholeCounty[c] = 1\n",
    "    #    plotPoly(countyGeom[c])\n",
    "    #if countyPop[c] < minCountyRatio*avgDistrictPop:  #small counties will naturally be unsplit.\n",
    "    #    wholeCounty[c] = 1\n",
    "plotPoly(MAP)\n",
    "plt.show()\n",
    "#print(\"there are a total of\",np.sum(wholeCounty),\"small or perfect counties that we will keep whole in Home Districts\")\n",
    "#for t in range(nTracts):\n",
    "#    if isSkippedTract == 0:\n",
    "#        if wholeCounty[countyNo[t]] == 1:  #this tract is part of a whole county per Article XI.3.c.2\n",
    "#            lockedTract[t] = 1             # ... or in a county that is so small we are keeping that county whole"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "732d8c17-022d-4fe9-b36d-2a15748d8d41",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for i,v in enumerate(skipList):\n",
    "    plotPoly(tractGeom[v])\n",
    "    plotCenter(v+0.1*i,tractCP[v])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "36f869cf-1af7-4c5c-9517-ac05860c7916",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "first read in vtd nbrs. These might slightly differ near Sandusky with how we connected units up there\n"
     ]
    }
   ],
   "source": [
    "print(\"first read in vtd nbrs. These might slightly differ near Sandusky with how we connected units up there\")\n",
    "infile2 = \"./state_map_files/OHvtdNbrsWithIslandNbrs.csv\"\n",
    "VTDtopDF = pd.read_csv(infile2)\n",
    "VTDnListString = VTDtopDF[\"vtdNbrs\"]\n",
    "vtdNbrs = [ast.literal_eval(VTDnListString[v]) for v in range(nVTDs)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "b84011eb-1f8c-4d81-9281-88a6dc62552b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now import the all-muni vtd - unit topology \n"
     ]
    }
   ],
   "source": [
    "print(\"Now import the all-muni vtd - unit topology \")  #these already split noncontigs and oversized munis, connected islands. Ready to rock\n",
    "infile = \"./state_map_files/OH15muni-unitTopologies_30Dec24.csv\"\n",
    "topologyDF = pd.read_csv(infile)\n",
    "muniPop = topologyDF[\"unitPop\"].to_list()\n",
    "nListString = topologyDF[\"unitNbrs\"]\n",
    "muniVTDlistString = topologyDF[\"unitVTDlist\"]\n",
    "muniCountyNo = topologyDF[\"unitCountyNo\"].to_list()\n",
    "muniCPx = topologyDF[\"centroid x\"].to_list()\n",
    "muniCPy = topologyDF[\"centroid y\"].to_list()\n",
    "nMunis = len(muniPop)\n",
    "muniNbrs = [ast.literal_eval(nListString[m]) for m in range(nMunis)]\n",
    "muniVTDlist = [ast.literal_eval(muniVTDlistString[m]) for m in range(nMunis)]\n",
    "borderUnits = list()\n",
    "onBorder = topologyDF[\"onBorder\"].to_list()\n",
    "for m in range(nMunis):\n",
    "    if onBorder[m] == 1:\n",
    "        borderUnits.append(m)\n",
    "countyUnitList = [list() for c in range(nCounties)]\n",
    "for m in range(nMunis):\n",
    "    countyUnitList[muniCountyNo[m]].append(m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "40325309-f2c2-436e-a31c-b293c3333d6e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For this 5-city code, we will break up all but the 5 most populous units. First confirm their locations and pops\n",
      "198 374054.0 unit no and pop\n",
      "158 329564.0 unit no and pop\n",
      "106 273926.0 unit no and pop\n",
      "119 190474.0 unit no and pop\n",
      "9 147110.0 unit no and pop\n"
     ]
    },
    {
     "data": {
      "image/png": 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TtacCSQ9uJ8HzB9q2jGLLtBi6nTEc8AdScqwW4+gbxLalkJC9iIS0ycTnVnKss4fdzkJyRoVRX3eColGb6GxvwBUYSVDVtZTsPMH4G4d6tIOrX4Fl8eLFFBUV9Wm74447yM7O5uGHHx6QsAJ/u6m3tLSUL3zhCwPSn4iIyGD44fFqMkMc7PG0M70hn+uiQjhysIeOSCsY+3A6F/KKqwFbXDwrK2uJit5LT2QCzSEziHj/fdZHB3OgYynpbXZmJHlwhsdT1eTHERvPwuvH8pdH7mZGnA975HiaPU48NaeYFRBCYM2NeNNTWN/WTW3XVuy2RmKe/TpRd3wb2wj9lm2/RhUeHk5OTk6fttDQUKKjo3vbq6urqa6u7l0dKSoqIjw8nLS0NKKiooC/BZ8VK1Zw7733AvDQQw+xfPly0tPTqays5JFHHsFms7Fy5coLHqCIiMhgWREfyUfuVjxtx9jc3c1rJW68tlDuKn8Od+3VHPQX4E4rx+Gay/ZxPURZZ3KzcYLOvXv5n0kGJR055NZvY0xQBx2BY/EYMXzxCwuwWv92i2nEvB6KAsPpObGTz2xvwxcYTqDdwo7QsYRsySc5YQ5GUA1pvjZeL5rN8o/+SvDoRbS3eQiLDCPUFTG0EzSABjyG/exnP+PRRx/tfb1gwQIAnn/+eW6//XYASktLqa+v792noqKClStX0tDQQGxsLPPnz2fHjh3ExsYOdHkiIiIDJqmqg8v2bGZs64t01DXzftoC5sZ8RIgjlkdCM5i5t4P0I5kEnGohaUwqE1KS2NYeS6JrA6GtJxlf+hELG5Opt/lIToijovg9fh0eRWZKIhagJfFb/Ie7BmtSJQtzf8tE22V0jB1H8KatZHS5WdDVw/fTD/B+aCqjy20sf/8bbHr9Vo411RI/NpxbHnxkqKdowFiMf/yu1TDl8XhwuVy43W6cTudQlyMiIiOc0dND54EDeO0xVFRX43n9Bdqymjma2cR14Wk4D2zjsGciFWm3EGZv47BlEvddP56NR2rZeKCGmUEOMhv+SGJgFYExl/PmwaPsTZ5LfEsJd6c1ELToK2CxAPD47/djq/2I2KoSqoNqGWebisvlItP/Ek3hDna5R1HfkUmP0YnLZeAOrqaIwyTHpvKT5c8M8UydWX8+vxVYRERE+qmjYDs9W39BSWUM7px5/DrFzZyaIqa315Jmb6LGE8afq1JxzV/E5V0dTL7uht5jexo6ePOp75M8cSPHPWMoLsvmtbQcSAvlB2VNzEoJIjS2DnxemPFFGivbaKxq4y8FBVRV7+Zfs64kKjwG6+wo7PZ2jO5uXn32NTLSx2ENC8Tv6SSmLZixt88jKHDgvtE7GPrz+T0y78wREREZLGU7CAquwzMaOlLmEdm6gUfrqvCHZlKXMo3agA6KDmxj1skSIqZnYLf3/bVke3QwM5d+ln0fBtHuhvZOuKWxmKTgjcS1p2KvD4RxKyByFABRSaFEJYVy/5SluL2zibSEYQ20YbFZgb/dG3rb/ffScbiRkyWlHDDKqZpoZewF/Vqg+SiwiIiI9Mfe32Fc/lV8dZvJcazDYvVxyDefyKxl7N/3PvVdJYya9nma8/zERoyh2tvMxH843Ofx4t3TgN8L869dSFhxMYU1DTSG3kVNVjRbejzclTH/E382wGYlJiTytCVZg+2ETo2jO6aSsI54kiNTCLKbe3Wlv3RJSERE5FxVfAS2QEj8+w//1hyA9gYYteATu/b4e+jydRFoC8Ru7bs+4O/xYbFZsfz9PpVLVX8+v0fYgpGIiMgg6OmCV+4Aq/1/w0pDKbQ3njasANitdkICQj4RVgCsdtslH1b6S5eEREREzmbXWlj0DfB1gWFA3WForYHMy4e6skuGVlhERETOJmM+NJSAtwX2/wkMv8LKRaYVFhERkbNJmvoPL2YPWRmXMq2wiIiIiOkpsIiIiIjpKbCIiIiI6SmwiIiIiOkpsIiIiIjpKbCIiIiI6SmwiIiIiOkpsIiIiIjpKbCIiIiI6SmwiIiIiOkpsIiIiIjpKbCIiIiI6SmwiIiIiOkpsIiIiIjpKbCIiIiI6SmwiIiIiOkpsIiIiIjpKbCIiIiI6SmwiIiIiOkpsIiIiIjpKbCIiIiI6SmwiIiIiOkpsIiIiIjpKbCIiIiI6SmwiIiIiOkpsIiIiIwQht+gze2lq6NnqEsZcPahLkBEREQuXPHOauyBVpwxwVQeaSY7LwGrzUqAw0ZnWzdVpW56unyMnRE/1KWeFwUWERGRESAmJQyb3UpEfAjhkUF89PZJSvJrWPalHKpK3EQlhmLYh++FFQUWERGR4ai1Fjqa8VXu5bgllTG5c9j0p700l/nImp1AbFoY9oAq3n7qh4yd8wUMA7LzEoa66vOmwCIiIjKc5P8KOprh2CYIiab9RD7Ppn6DnuouImwdeMYmUfX7oyxcFc1bRWsZtWgajUkHSbTMJCgkYIiLP38KLCIiIsPJ9Nvh2GaY9Fk4vgUjOI4rreW4ogKwO70EHHiD/5q+kg+K/8C/rvw3osLD2HvkB4SOsWGxXjvU1Z+34XsxS0RE5BLlz7gMj8UJh14nxBfA7KJCsspOUldwjOqam1lWZeezUV9gV8VRcmNzCXdNxzB8lB74E++UVVLW4R3qIfSbVlhERESGGY/Hw/a3XmZS9FzC7Ccp7DlOSWkoNF1FY2gDbksokZFB+E5s5Ke/3EnC1EwSEq6nYN132NnZwu9y5jKhophrxqcTGBhEc3Mzs2bNGuphnZFWWERERIaZsLAwknPyOGz5JacCfThyriQrLYn25H3MPPUGn81o4t9njuUyWx0TUmdSWX6KX77+S+xPvsacslN8Z0Iy2ZEvYrMdpfXgVkKsjqEe0llphUVERGSYsdvtREZGUbbvdpyz5mDd2kBQTiSuYB+nFhew7UATRf/9OxLScuk8UMLWmATsCeOw3DCb5OZtrC28ktkNX8AVGkZ0Rjytx/0wY6hHdWZaYRERERmGUlNT+cw/38vBrR8RvDKDgxNieSS6gbetUYSE7sHjLuYPJzLxx0bwz8H7iGyvxBLnpyImk5jaBlqjx/PRthAOr7dQfqib7S8XU7OraqiH9am0wiIiIjJMWa02Uj+zkA+ObaHoxCFC3VcSXHWKwmgXowOr+fyxLhLbiwlLbsU5ykJw8v+jObiGyT0Z7KloY96NEWz61cukBDqJKkkmJDGPlv3H6YwtxRoQRHTU/KEeYi8FFhERkWHMsFtYPu1zLElvpuIH/0NnYCtVhzuIDJtByLgsmsb8E3X+E7Qd9FN85LdMnJZIrf85op3BfPRmCm3Jo7EbfyXJlUfYgs9ysmAjp0p2kpaWTXTUUI/ufymwiIiIDGPN3ma2V27n0P5NfL7wGKFpQVSnLsIWkk58Vhx0vEZ3fRvdPVPITc3EEneMdx3RzO2KZkzjVuITx1EWHE1wzz74YzGeVgenakZzMquCJa5O4pxBQz1EQIFFRERkWHO7y8msO0a8MxTLTdn8qC4Sf0cIlwedojO/iNHxJwiMzKHAUUZtUAneumymRl9O5eY9vDYzF1tkAgY3EeyxE9vqZl5NBRWWMOoYQ/f+at4qquKa3ERunpmKw24bsnEqsIiIiAxjnwlJpWf+NdDTQo11NV8b08G+428R2XMZnR47HfHXsntfIXUTpxHaGMmm9lF0VZ1ibijMrs9lVKaNtuQYXjzwHDHVMdTFx2AEtBPesJ+xE2/n83PSCQ+yY7NYhnSc+paQiIjIcNbdjj0wDHfVbio8U2lu7eKvUQE0Be2nfUwExR1eSkZNo+HgKRKqTpLpaeLaxhMYQQnMnDiLk501BFgsRFlsnEzK4nhgAjNOtHBn50HG7PkeyycncXlWHHbb0EYGrbCIiIgMZ65UKH6LyuOv4m6bSJfnMq7JaSB7wSQ+dNv5l/GL+Nb+Mipr/NRExxMafIzWJpgUEES4NZKOoHSmR6WQt/DbvFTdwfyGaialJxLQU4YjxzwPZ7mguPT4449jsVj48pe/3Nv285//nMsvvxyn04nFYqG5ufmc+vrpT39KRkYGQUFBzJ49m127dl1IaSIiIpeGuGzIvoZu40ZSJyURHF/ImLg4umrKaKzexx9K3qfa7yZ9bhrpE1ykp5wk8voF/Dy+hU3BPlZlz6CjO5RXD3tI7bKQN2saYZddhmPRKojNGurR9TrvwLJ7927Wrl1Lbm5un/b29naWLVvG17/+9XPu6/e//z0PPvggjzzyCAUFBUyePJmrrrqK2tra8y1PRETkkpKzcCkhm9KZlPpvRL6VSVjwZSx2ljCVj7jX9ks+67+NBSnH+VxSAoGdE+jqnklRQzt3vLyH1/dVMis6nFgT3yliMQzD6O9Bra2tTJs2jaeffprHHnuMKVOm8OMf/7jPPps2bWLRokU0NTURERFxxv5mz57NzJkzeeqppwDw+/2kpqZy33338bWvfe2s9Xg8HlwuF263G6fT2d/hiIiIDHuGYeBv6aK7rgNLgBVH2v9+HtbWvUtwUAphYRNoaSmis7OSYOdiPg4Ahh8MDEIC7QTaL15o6c/n93lVdc8993DNNdewZMmS8yrwH3V1dZGfn9+nL6vVypIlS9i+fftpj/F6vXg8nj6biIjIpcxisWBzOggaHdEnrABERc7D7dlLT08LdXXriIqaR3hQAM6/b66QACJCAi9qWOmvflf28ssvU1BQwJo1awakgPr6enw+H/Hx8X3a4+Pjqa6uPu0xa9asweVy9W6pqakDUouIiMhIZLeHkZhwIzW1bxIUnILdHj7UJfVbvwJLeXk5999/Py+99BJBQUP35LvVq1fjdrt7t/Ly8iGrRUREZDiw2YJISf5nkpNuHupSzku/vtacn59PbW0t06ZN623z+Xx88MEHPPXUU3i9Xmy2/j0FLyYmBpvNRk1NTZ/2mpoaEhISTnuMw+HA4XD06++IiIjI8NWvFZbFixdTVFREYWFh7zZjxgxWrVpFYWFhv8MKQGBgINOnT2f9+vW9bX6/n/Xr15OXl9fv/kRERGTk6dcKS3h4ODk5OX3aQkNDiY6O7m2vrq6murqakpISAIqKiggPDyctLY2oqL/97OPixYtZsWIF9957LwAPPvggt912GzNmzGDWrFn8+Mc/pq2tjTvuuOOCBygiIiLD34A/6fZnP/sZjz76aO/rBQsWAPD8889z++23A1BaWkp9fX3vPjfffDN1dXV885vfpLq6milTpvDOO+984kZcERERuTSd13NYzEbPYRERERl+Bv05LCIiIiIXkwKLiIiImJ4Ci4iIiJieAouIiIiYngKLiIiImJ4Ci4iIiJieAouIiIiYngKLiIiImJ4Ci4iIiJieAouIiIiYngKLiIiImJ4Ci4iIiJieAouIiIiYngKLiIiImJ4Ci4iIiJieAouIiIiYngKLiIiImJ4Ci4iIiJieAouIiIiYngKLiIiImJ4Ci4iIiJieAouIiIiYngKLiIiImJ4Ci4iIiJieAouIiIiYngKLiIiImJ4Ci4iIiJieAouIiIiYngKLiIiImJ4Ci4iIiJieAouIiIiYngKLiIiImJ4Ci4iIiJieAouIiIiYngKLiIiImJ4Ci4iIiJieAouIiIiYngKLiIiImJ4Ci4iIiJieAouIiIiYngKLiIiImJ4Ci4iIiJieAouIiIiYngKLiIiImJ4Ci4iIiJieAouIiIiYngKLiIiImJ4Ci4iIiJieAouIiIiYngKLiIiImJ4Ci4iIiJieAouIiIiY3gUFlscffxyLxcKXv/zl3rbOzk7uueceoqOjCQsL46abbqKmpuaM/dx+++1YLJY+27Jlyy6kNBERERlBzjuw7N69m7Vr15Kbm9un/YEHHuCNN97glVdeYfPmzVRWVnLjjTeetb9ly5ZRVVXVu/3ud78739JERERkhDmvwNLa2sqqVat49tlniYyM7G13u90899xz/OhHP+KKK65g+vTpPP/883z44Yfs2LHjjH06HA4SEhJ6t3/sV0RERC5t5xVY7rnnHq655hqWLFnSpz0/P5/u7u4+7dnZ2aSlpbF9+/Yz9rlp0ybi4uLIysri7rvvpqGh4VP39Xq9eDyePpuIiIiMXPb+HvDyyy9TUFDA7t27P/FedXU1gYGBRERE9GmPj4+nurr6U/tctmwZN954I6NGjaK0tJSvf/3rXH311Wzfvh2bzfaJ/desWcOjjz7a39JFRERkmOpXYCkvL+f+++9n3bp1BAUFDVgRt9xyS+9/T5o0idzcXEaPHs2mTZtYvHjxJ/ZfvXo1Dz74YO9rj8dDamrqgNUjIiIi5tKvS0L5+fnU1tYybdo07HY7drudzZs385Of/AS73U58fDxdXV00Nzf3Oa6mpoaEhIRz/juZmZnExMRQUlJy2vcdDgdOp7PPJiIiIiNXv1ZYFi9eTFFRUZ+2O+64g+zsbB5++GFSU1MJCAhg/fr13HTTTQAUFxdTVlZGXl7eOf+diooKGhoaSExM7E95IiIiMkL1K7CEh4eTk5PTpy00NJTo6Oje9jvvvJMHH3yQqKgonE4n9913H3l5ecyZM6f3mOzsbNasWcOKFStobW3l0Ucf5aabbiIhIYHS0lK++tWvMmbMGK666qoBGKKIiIgMd/2+6fZsnnjiCaxWKzfddBNer5errrqKp59+us8+xcXFuN1uAGw2G/v27ePXv/41zc3NJCUlsXTpUr7zne/gcDgGujwREREZhiyGYRhDXcSF8ng8uFwu3G637mcREREZJvrz+a3fEhIRERHTU2ARERER01NgEREREdNTYBERERHTU2ARERER01NgEREREdNTYBERERHTU2ARERER01NgEREREdNTYBERERHTU2ARERER01NgEREREdNTYBERERHTU2ARERER01NgEREREdNTYBERERHTU2ARERER01NgEREREdNTYBERERHTU2ARERER01NgEREREdNTYBERERHTU2ARERER01NgEREREdNTYBERERHTU2ARERER01NgEREREdNTYBERERHTU2ARERER01NgEREREdNTYBERERHTU2ARERER01NgEREREdNTYBERERHTU2ARERER01NgEREREdNTYBERERHTU2ARERER01NgEREREdNTYBERERHTU2ARERER01NgEREREdNTYBERERHTU2ARERER01NgEREREdNTYBERERHTU2ARERER01NgEREREdNTYBERERHTU2ARERER01NgEREREdO7oMDy+OOPY7FY+PKXv9zb1tnZyT333EN0dDRhYWHcdNNN1NTUnLEfwzD45je/SWJiIsHBwSxZsoSjR49eSGkiIiIygpx3YNm9ezdr164lNze3T/sDDzzAG2+8wSuvvMLmzZuprKzkxhtvPGNf3//+9/nJT37Cz372M3bu3EloaChXXXUVnZ2d51ueiIiIjCDnFVhaW1tZtWoVzz77LJGRkb3tbreb5557jh/96EdcccUVTJ8+neeff54PP/yQHTt2nLYvwzD48Y9/zH/8x39w/fXXk5ubywsvvEBlZSV/+ctfzmtQIiIiMrKcV2C55557uOaaa1iyZEmf9vz8fLq7u/u0Z2dnk5aWxvbt20/b1/Hjx6muru5zjMvlYvbs2Z96jIiIiFxa7P094OWXX6agoIDdu3d/4r3q6moCAwOJiIjo0x4fH091dfVp+/u4PT4+/pyP8Xq9eL3e3tcej6c/QxAREZFhpl8rLOXl5dx///289NJLBAUFDVZNZ7VmzRpcLlfvlpqaOmS1iIiIyODrV2DJz8+ntraWadOmYbfbsdvtbN68mZ/85CfY7Xbi4+Pp6uqiubm5z3E1NTUkJCScts+P2//vN4nOdMzq1atxu929W3l5eX+GISIiIsNMvwLL4sWLKSoqorCwsHebMWMGq1at6v3vgIAA1q9f33tMcXExZWVl5OXlnbbPUaNGkZCQ0OcYj8fDzp07P/UYh8OB0+nss4mIiMjI1a97WMLDw8nJyenTFhoaSnR0dG/7nXfeyYMPPkhUVBROp5P77ruPvLw85syZ03tMdnY2a9asYcWKFb3PcXnssccYO3Yso0aN4j//8z9JSkrihhtuuPARioiIyLDX75tuz+aJJ57AarVy00034fV6ueqqq3j66af77FNcXIzb7e59/dWvfpW2tja+9KUv0dzczPz583nnnXeG9D4ZERERMQ+LYRjGUBdxoTweDy6XC7fbrctDIiIiw0R/Pr/1W0IiIiJiegosIiIiYnoKLCIiImJ6CiwiIiJiegosIiIiYnoKLCIiImJ6CiwiIiJiegosIiIiYnoKLCIiImJ6CiwiIiJiegosIiIiYnoD/uOHcmnqqmzF39IFNitBYyKGuhwRERlhtMIiA8Jb0gx2K0Znz1CXIiIiI5ACiwwIS4AVi8WCJcj2qft4vbU0Nm6jo6P8IlYmIiIjgQKL9JthGBiGr/d1V2UrjkwX/o5uuqvaTntMU1MR27Zcid8bSltbycUqVURERgjdwyLnrKbmTSyWAGy2IOobNpI17lsAdOyvJ3xBCnU/L6J4oofo/HpOHiohwt3J2KvnUHs0gMbWI3R4nFRs+hXRX1wBMUM7FhERGV60wiLnLDgkg+DgNKKiLsNmDcHv9wJgjwzC19pN1C1ZpBOLu7CK+kPlBIcEUZ9/AvY+j7VsM+/bZnJgzkzKOkOGdiAiIjLsKLDIWfV0dWEYBs7wHGy2IOrq3iPUH0Z1xSsABI5y0VPdRtDYSDKWTyarJ4nrb/48RzvSqYwcxbNd4/izs4DRYy9np6WRAGfoEI9IRESGG10Skk/YXb2bZm8zroBwnMe97PjzH0i/9gtMnzeZXx7ZwGc2F5O6dCaB1fV02VrxrDtJxPJM9pU38W7B+1wbd4iiI4uIHJeEry6fO6Z3YS1NJyVzGu4xVxBoU04WEZH+UWCRPtq723nz2JvMbmujwl1G5NQvYc8czd0lHpzNBxl3NJwJ6xtJXpCKpamQHRk+TsyKZEp7J+E1hxhbe4DazHqyrFsItM0BfzddjmASbvg2Nb5wDlc0c01u4lAPU0REhhkFlkvcqdZTlDaXYrVYae1uJSYohpDmEN5qO0xw9ViCW94ktbmB2+baKSpJAXcILXNXcfREKUdTL2dZVBhOdxc791QRZg1mo28Z/zVnCgcPvU1NTTh1Fg+2piBGt4YzPtHBTdNdQz1kEREZhhRYLmG7qnbxwsEXSAxN5KZxN7Hn9zXsaaslonEUX5pcgyuwhXJLLl2jq4kpL2Fvcy0NGbt5IxTyQqKJDruDcLsNZ1gg2423cFks7G/o4K2tBoG2JPytZSyYOoHx48cP9VBFRGSYU2C5hLV2t3JL9i1YsNDl62JBQjUnD+ykKyGZ+CP7icuJJqyriIrjuygYtQKXL4zxZbOZ3/YO72bNZU+QjXc7tnOVtQhP+x4WO2awfNJEQgPaqd17klFjJ1FRUaHAIiIiF0yB5RKW4crghPsER5qOEGAN4IS1gMz2U+S4Oon8p69hqV1PdGUhrQlJFHh34ku8llCfjSrXzYRH2nCEt/LZlESaNni4p2IuRqMfj/MY3aP2keBczBavh+0tUYQ2tTA3MnyohysiIsOYAsslLNOVSaYrkyvSrgDgvfBUumZ1sWHTj7E89h2soQ4i3M2UpUxh+fwZ2HxWyr1WosPCaOoajd8PW177LV2NgeQ2xRETG0ZGpwvPb/IpmdPBbqOH1SuyONTVPcQjFRGR4U7fL5Vei1IXERccR0TnKHyfvxmbK5mUp14hI+0GjM7pnLQH8tn0SSRU+lloDyKrxou3MYkuPDwf2MHX20N5yNfOh+k3U9AYzb+99jO2fH01FZ1dQz00EREZ5rTCIr28H+5kTHkZEy+7j5CcSWws7+aVlzcTbNjZFBLA0sZ0wsMiSL/9BgC6f/saObMjWDjzW5w6Wc6G995iVHIiJ+r3keJPp23eLURY6hnbuIWSnjbiYqfhdE4a2kGKiMiwpMAivQLTUjG6u/Bs/oCC379E0IQc0qKisPqD+PlnrqDolbeoqnLT8mYbRfvWkzoll3HOsdQdLyU0zMVnkqqxdcaRG+XmpCOM4/44gsdFcuyYh+CQSuy2cTidQz1KEREZjhRYBABPfR17P9xEqCuCyp42gjLSyZ4ylZQJOQB0ezsJH5dAxuRpeNvbSb5qCvaAgD597LLdRdWJfFIDghhTV4g7cjw585NJSEgYiiGJiMgIosAiABzZvoWaYyV0trbyT//5GNv/9DLejvbe9+tOHic2fRQAjpDT/3jhrJRMCsLjSZp5A5GOAJZclMpFRORSoMAiAMxYfiPJ2ROpKjlC46kKvG1tGIbBicJ8DADDIDQi8qz9THPphw1FRGTgWQzDMIa6iAvl8XhwuVy43W6cuknivPl9Prq9Xro7OwiNjMJisQx1SSIiMoL15/NbKyzSy2qz4QgJ+dRLPiIiIkNFz2ERERER01NgEREREdNTYBERERHTU2ARERER01NgEREREdNTYBERERHTU2ARERER01NgEREREdNTYBERERHTU2ARERER01NgEREREdNTYBERERHTU2ARERER01NgEREREdNTYBERERHTU2ARERER01NgEREREdNTYBERERHTU2ARERER0+tXYHnmmWfIzc3F6XTidDrJy8vj7bff7n2/tLSUFStWEBsbi9Pp5HOf+xw1NTVn7PNb3/oWFoulz5adnX1+oxEREZERqV+BJSUlhccff5z8/Hw++ugjrrjiCq6//noOHDhAW1sbS5cuxWKxsGHDBrZt20ZXVxfLly/H7/efsd+JEydSVVXVu23duvWCBiUiIiIji70/Oy9fvrzP6+9+97s888wz7Nixg1OnTnHixAn27NmD0+kE4Ne//jWRkZFs2LCBJUuWfHoRdjsJCQnnUb6IiIhcCs77Hhafz8fLL79MW1sbeXl5eL1eLBYLDoejd5+goCCsVutZV0yOHj1KUlISmZmZrFq1irKysjPu7/V68Xg8fTYREREZufodWIqKiggLC8PhcHDXXXfx5z//mQkTJjBnzhxCQ0N5+OGHaW9vp62tjYceegifz0dVVdWn9jd79mx+9atf8c477/DMM89w/PhxLrvsMlpaWj71mDVr1uByuXq31NTU/g5DREREhhGLYRhGfw7o6uqirKwMt9vNH//4R37xi1+wefNmJkyYwHvvvcfdd9/N8ePHsVqtrFy5koMHDzJr1iyeeeaZc+q/ubmZ9PR0fvSjH3HnnXeedh+v14vX6+197fF4SE1Nxe12916OEhEREXPzeDy4XK5z+vzu1z0sAIGBgYwZMwaA6dOns3v3bp588knWrl3L0qVLKS0tpb6+HrvdTkREBAkJCWRmZp5z/xEREYwbN46SkpJP3cfhcPS59CQiIiIj2wU/h8Xv9/dZ7QCIiYkhIiKCDRs2UFtby3XXXXfO/bW2tlJaWkpiYuKFliYiIiIjRL9WWFavXs3VV19NWloaLS0t/Pa3v2XTpk28++67ADz//POMHz+e2NhYtm/fzv33388DDzxAVlZWbx+LFy9mxYoV3HvvvQA89NBDLF++nPT0dCorK3nkkUew2WysXLlyAIcpIiIiw1m/AkttbS233norVVVVuFwucnNzeffdd7nyyisBKC4uZvXq1TQ2NpKRkcE3vvENHnjggT59fHzJ6GMVFRWsXLmShoYGYmNjmT9/Pjt27CA2NnYAhiciIiIjQb9vujWj/ty0IyIiIubQn89v/ZaQiIiImJ4Ci4iIiJieAouIiIiYngKLiIiImJ4Ci4iIiJieAouIiIiYngKLiIiImJ4Ci4iIiJieAouIiIiYngKLiIiImJ4Ci4iIiJieAouIiIiYngKLiIiImJ4Ci4iIiJieAouIiIiYngKLiIiImJ4Ci4iIiJieAouIiIiYngKLiIiImJ4Ci4iIiJieAouIiIiYngKLiIiImJ4Ci4iIiJieAouIiIiYngKLiIiImJ4Ci4iIiJieAouIiIiYngKLiIiImJ59qAu41JV7ytlYtZdbs67t0+6u66DmhBuLxUJaXDD+jh7sLgcBCaFDVKmIiMjQUWC5mPx+6GrBcDhpfOstPvLBoe42XogIJzXGw6JoZ++ujaXV+Pfk0+HxcsIeQtj1C9j/0SliJsUyPT1yCAchIiJy8SmwXCRlzQ3E7fofAlNnUF73Hid2Q70ji9rYDDKjg2h2F1BY4iPYUUVC5iSaqv9IjDOM0Eg/3T4Xz63/b6Jbl2CL+QtG2lewWCxDPSQREZGLRoHlIqnGwbZqJwHlv6FplIu2qUnc/NGL5G0L4zekYVgX4EibQ2XhBja3efn80i8REpJKa+sR1h1+itpT7YQYe5iYnNUnrBQdzCfTm0rQaBc2p2MIRygiIjJ4FFguErvFwr7m+bSNXsycwDIOxPopzUwlckIIl0UbbK3Zx8GDpwifBKHR6ew4tZEcZxyHd3+FJTm/4s0WD5+tiyek1IcR34X7jTd5r2oz5REL6Um1sHT/FqZGBUP2Z4Z6qCIiIgNO3xK6SMYEdWPMO8m85KPMiY4kozuT1tB6eja9R2qjQWxsGq3BrbzZfQVp/kMsGLWC4CI7E1N+wMma5/l2iY+ALWvpfPM2qv7jCjZuaaD51HKa65MI6zxJsLuWbd1jh3qYIiIig0IrLBdJdcmbPJJ9LcGhEezL/y9m+Eqp75hLaWYagY2l3H3Lf9Dj66G69jDNDS4s7QY99fXUlG6HsV2U+56luaqJsglXYh8/jf0eG3mdNSxdNpldJ/0ccCTjq6mhfXQgVmsAQUFJQz1kERGRAaPAMojaT55i/18KSVgyBwdXUbzvDUZnf4Zg51ROeU4Qk9SK13kcZ2I6mzffj7WjnQgjj+jAMN6KysSRMhdnWzIl2w7R1tNKyBWJFDj9pAQHU+Pp4Zr/t5A3//pHxo1LZ9KkxTz73GO8Zs+g6dgB5s9YQW7uZUM9BSIiIgNCgWUQFf1mHc0n9lMf00F85AxaG6bz4d4/44kK54BxE9GxHxATfpDKgy3Eh+USUrKesGUBnKr8kLoNwVREB+Jz+6h09TAlIZw/B8RwQ/efCGkP5IQzmKd+9zrT/KPhaCh/3f84/pM2GorrMMKTqQ4qJympnpiYmKGeBhERkQumwDLAjh/cz/69e2msDKWu4RjW4Goy9r+PJ3ArNS0RnMpZyLEqH3mzLOzZ68A+ZzGd+w+RWr+RU5FT2H+yC09PCKOK1zPXH82u0HTsQYegbDbfjComvnw3h+OjsNgiKO7wkhkwn5C4TLoaGpg7bxRx7dBRXk5IVjZBQUFDPR0iIiIDQoFlgKVnjee9n/6QnlAHWycfZ1xPFq2FYTT7Da69PInGtpPkjJlARVkraVUO7p5yN9/Pf4D2DgfJRjPxNW5Cbd00R02jsbqMicYWYvxJHLRXU9GTy8SOf2OnZwuWjjZWJl7OtiM7+ZPtMLaETn551T0E2gKHegpEREQGnL4ldBbu9m5+seUYf9lz6pz2t9psTFxwBVNnLeRh3xRGdTfgtB7h3mgH1p2HWebuJrPSh7vGysLJs2ioqyHcO4bWxlmkNL/L66HbKYqsYOHVkwiveYejqbHE+rO5MjSFaxu2kDenjXmtQfzLUQel7xVQ64iiNczH0rTrePXoq/j8vkGeERERkYvPYhiGMdRFXCiPx4PL5cLtduN0Os9+QD9tK6lnT+0emluCWTJ2PHMyo896TFdnB//93G+4LLSVVkscLftKSYg+wNwJKfjdfozkuXTV7KQwsZP2mgzeOB5Nekc0k201bJvQgzUklaP1PkKbqvma9UWM1Kk0OgtIdC0Ej8Gp40c5XD6RD8OamDNjKrcvuoOCmgJGR4zG5XAN+ByIiIgMtP58fuuS0DmYNyaGDdWHOdxRxbEjh+iJvIX5keGfur/h81F5+xdZGTwNz9gU2ls38cGk65kRFkZYy0HG+47SGRJOfehW5s56g4IdP2GFN4AdnnJOlVi5bGs6tZ8bzYzi58l1HCL19lchLI5Rhh+3Zw+HP1iLP/gYOce8rPzpS+w6sZMX3n+KuIxMpsVPu4gzIyIicnFohaUfvrXrp3itESSHJ3PPuIVn/D0fv9fLE+t2kJAUzev793JNezOdYZNo8ruZm7KOWEcDkaETiZ/ydQoKHqS+/jC1dZl4G2eT4W3hsowm7ElJWOfe8Ym+WxrraaqsJC0nt7dtX8Fufthay/1BbeQEWekIG4crM/cTx4qIiJhFfz6/FVj6wW/42VG5g4rWCg41HsJhc5AVmcWE6AmMixz3iQDT1N3Dsf37aMjfzvicPEKbfJw8Wk9E02F6tr1I0mMraU/N5ljZISZMuJUPP3yF9uBwuoLqSXPkkDf5qk+t5VjBbtJzp2Kz29l5YCMfefaSMOpWshw2Dr71JCFH9tMz8Z+54XM3DNp8iIiIXAhdEhokVouVuclze18bhsHBhoPsrNrJkaYjTI+fTlLY/z5hNjLAzvSp0zCmTKXlvXX4PN1kJAVS/fTPGf32GwSOGkMo4Agdzb6i75KQcA0pKUE4ndcREBB5xlrsgYEYhkFXj5etJzaTNDqL1qZ8dm4LprphAv98593sOFE/WFMhIiJyUWmFZQD0+HvYVL6JZm8z4yLHkbz+II6UVIzuLozubjDA6PJic7nwd3QSOm8etrDQC/qbp4oPEZWcwqM73iEgNpac4GYO1ReSVB1JWslcToZaiQwN5HO3TxqYQYqIiAwwrbBcZHarnSXpSzjceJj9JduxHNxPqt2O7e9PmbWGBBM4YTwBKSlnvO+lP3qS0li9o4Bbx8wiKTGJI22dXJEyj7LaE6SFxZJkt+Fp6ByQvyUiIjLUtMIyTHX4/OR72nq/rfSbyno+Gx9FsE2P1hERkeFBKyyXgGCblSpvN91+g7fr3VwR5VRYERGREUufcMNYoiOA7x2r5KoYJ8lBeiS/iIiMXFphGcbmR4af8QF2IiIiI4VWWERERMT0+hVYnnnmGXJzc3E6nTidTvLy8nj77bd73y8tLWXFihXExsbidDr53Oc+R01NzVn7/elPf0pGRgZBQUHMnj2bXbt29X8kIiIiMmL1K7CkpKTw+OOPk5+fz0cffcQVV1zB9ddfz4EDB2hra2Pp0qVYLBY2bNjAtm3b6OrqYvny5fj9/k/t8/e//z0PPvggjzzyCAUFBUyePJmrrrqK2traCx6ciIiIjAwX/LXmqKgofvCDH5CamsrVV19NU1NT71eT3G43kZGRvPfeeyxZsuS0x8+ePZuZM2fy1FNPAeD3+0lNTeW+++7ja1/72jnVcCl+rVlERGS468/n93nfw+Lz+Xj55Zdpa2sjLy8Pr9eLxWLB4XD07hMUFITVamXr1q2n7aOrq4v8/Pw+YcZqtbJkyRK2b9/+qX/b6/Xi8Xj6bCIiIjJy9TuwFBUVERYWhsPh4K677uLPf/4zEyZMYM6cOYSGhvLwww/T3t5OW1sbDz30ED6fj6qqqtP2VV9fj8/nIz4+vk97fHw81dXVn1rDmjVrcLlcvVtqamp/hyEiIiLDSL8DS1ZWFoWFhezcuZO7776b2267jYMHDxIbG8srr7zCG2+8QVhYGC6Xi+bmZqZNm4bVOrBfRlq9ejVut7t3Ky8vH9D+RURExFz6/RyWwMBAxowZA8D06dPZvXs3Tz75JGvXrmXp0qWUlpZSX1+P3W4nIiKChIQEMjMzT9tXTEwMNpvtE98kqqmpISEh4VNrcDgcfS49iYiIyMh2wUsffr8fr9fbpy0mJoaIiAg2bNhAbW0t11133WmPDQwMZPr06axfv75Pf+vXrycvL+9CSxMREZERol8rLKtXr+bqq68mLS2NlpYWfvvb37Jp0ybeffddAJ5//nnGjx9PbGws27dv5/777+eBBx4gKyurt4/FixezYsUK7r33XgAefPBBbrvtNmbMmMGsWbP48Y9/TFtbG3fccccADlNERESGs34FltraWm699VaqqqpwuVzk5uby7rvvcuWVVwJQXFzM6tWraWxsJCMjg2984xs88MADffr4+JLRx26++Wbq6ur45je/SXV1NVOmTOGdd975xI24IiIicum64OewmIGewyIiIjL8XJTnsIiIiIhcLAosIiIiYnr9/lqzGX18VUtPvBURERk+Pv7cPpe7U0ZEYGlpaQHQE29FRESGoZaWFlwu1xn3GRE33fr9fiorKwkPD8disQx1ORfM4/GQmppKeXm5biJG8/F/aT760nx8kuakL81HX2aaD8MwaGlpISkp6axPxR8RKyxWq5WUlJShLmPAOZ3OIT+ZzETz0Zfmoy/NxydpTvrSfPRllvk428rKx3TTrYiIiJieAouIiIiYngKLCTkcDh555BH9wOPfaT760nz0pfn4JM1JX5qPvobrfIyIm25FRERkZNMKi4iIiJieAouIiIiYngKLiIiImJ4Ci4iIiJieAssQOHLkCNdffz0xMTE4nU7mz5/Pxo0bT7tvQ0MDKSkpWCwWmpubz9hvRkYGFoulz/b4448PwggG1mDNR2NjI6tWrcLpdBIREcGdd95Ja2vrIIxg4J1tThoaGli2bBlJSUk4HA5SU1O59957z/p7WiP1HDnf+Riu58jZ5mPv3r2sXLmS1NRUgoODGT9+PE8++eRZ+x2p58f5zsdIPT8A/v3f/53p06fjcDiYMmXKOfV7+eWXf+L8uOuuuwZhBKenwDIErr32Wnp6etiwYQP5+flMnjyZa6+9lurq6k/se+edd5Kbm3vOfX/729+mqqqqd7vvvvsGsvRBMVjzsWrVKg4cOMC6det48803+eCDD/jSl7400OUPirPNidVq5frrr+f111/nyJEj/OpXv+L9998/p388RuI5cr7zMVzPkbPNR35+PnFxcbz44oscOHCAb3zjG6xevZqnnnrqrH2PxPPjfOdjpJ4fH/viF7/IzTff3K++/+Vf/qXP+fH9739/IEs/M0Muqrq6OgMwPvjgg942j8djAMa6dev67Pv0008bCxcuNNavX28ARlNT0xn7Tk9PN5544olBqHrwDNZ8HDx40ACM3bt397a9/fbbhsViMU6dOjXg4xhI/ZmTf/Tkk08aKSkpZ+x7pJ8j/+hs8zFcz5HznY9/+7d/MxYtWnTGvi+l8+Ns83GpnB+PPPKIMXny5HPqe+HChcb9998/QJX2n1ZYLrLo6GiysrJ44YUXaGtro6enh7Vr1xIXF8f06dN79zt48CDf/va3eeGFF876g1D/6PHHHyc6OpqpU6fygx/8gJ6ensEYxoAZrPnYvn07ERERzJgxo7dtyZIlWK1Wdu7cOShjGSjnOif/qLKykldffZWFCxeetf+Reo78o3OZj+F6jpzPfAC43W6ioqLO2v+lcH7A2efjUjs/ztVLL71ETEwMOTk5rF69mvb29gGo+hwNWVS6hJWXlxvTp083LBaLYbPZjMTERKOgoKD3/c7OTiM3N9f4zW9+YxiGYWzcuPGcVlh++MMfGhs3bjT27t1rPPPMM0ZERITxwAMPDOZQBsRgzMd3v/tdY9y4cZ9oj42NNZ5++ukBH8NAO9ucfOyWW24xgoODDcBYvny50dHRccZ+R+o58rH+zMdwPkfOdT4+tm3bNsNutxvvvvvuGfsd6efHx85lPi6V86M/Kyxr16413nnnHWPfvn3Giy++aCQnJxsrVqwYwMrPTIFlgDz88MMGcMbt0KFDht/vN6677jrj6quvNrZu3Wrk5+cbd999t5GcnGxUVlYahmEYDzzwgHHzzTf39n2ugeX/eu655wy73W50dnYO5FDPyVDPhxn/sRnIOflYVVWVcejQIeO1114zJkyYYNx99939qmmknCMf6898mO0cGYz5MAzDKCoqMmJiYozvfOc7/a5ppJ0fhnHu83GpnB/9CSz/18eX50tKSi5wdOdGgWWA1NbWGocOHTrj5vV6jffff9+wWq2G2+3uc/yYMWOMNWvWGIZhGJMnTzasVqths9kMm81mWK1WAzBsNpvxzW9+85xr2r9/vwEYhw8fHtCxnouhno/nnnvOiIiI6NPW3d1t2Gw249VXXx2cQZ/FQM7J6WzZssUATvuP0qcZKefI6ZxtPsx2jgzGfBw4cMCIi4szvv71r59XTSPt/OjPfFwK54dhXFhgaW1tNQDjnXfeOa/j+8t+AVeT5B/ExsYSGxt71v0+vt73f+/DsFqt+P1+AP70pz/R0dHR+97u3bv54he/yJYtWxg9evQ511RYWIjVaiUuLu6cjxkoQz0feXl5NDc3k5+f33vddsOGDfj9fmbPnn1eY7pQAzknp/Pxe16v95xrGinnyOmcbT7Mdo4M9HwcOHCAK664gttuu43vfve751XTSDo/+jsfI/38GAiFhYUAJCYmDmi/n+qixCLpVVdXZ0RHRxs33nijUVhYaBQXFxsPPfSQERAQYBQWFp72mNNdAtm5c6eRlZVlVFRUGIZhGB9++KHxxBNPGIWFhUZpaanx4osvGrGxscatt956MYZ13gZrPgzDMJYtW2ZMnTrV2Llzp7F161Zj7NixxsqVKwd7SBfsXObkr3/9q/HLX/7SKCoqMo4fP268+eabxvjx44158+b19nMpnSPnMx+GMTzPkXOZj6KiIiM2Ntb4/Oc/b1RVVfVutbW1vf1cSufH+cyHYYzc88MwDOPo0aPGnj17jH/91381xo0bZ+zZs8fYs2eP4fV6DcMwjIqKCiMrK8vYuXOnYRiGUVJSYnz72982PvroI+P48ePGa6+9ZmRmZhoLFiy4aGNTYBkCu3fvNpYuXWpERUUZ4eHhxpw5c4y33nrrU/c/3Qf0x23Hjx83DMMw8vPzjdmzZxsul8sICgoyxo8fb3zve98bkmvP/TUY82EYhtHQ0GCsXLnSCAsLM5xOp3HHHXcYLS0tgziSgXO2OdmwYYORl5fX+/977NixxsMPP3zJniPnMx+GMXzPkbPNxyOPPHLaexzS09N797mUzo/zmQ/DGLnnh2H87SvKp5uTj8d//PhxAzA2btxoGIZhlJWVGQsWLDCioqIMh8NhjBkzxvjKV77yiUtPg8liGIZxcdZyRERERM6PnsMiIiIipqfAIiIiIqanwCIiIiKmp8AiIiIipqfAIiIiIqanwCIiIiKmp8AiIiIipqfAIiIiIqanwCIiIiKmp8AiIiIipqfAIiIiIqanwCIiIiKm9/8D/B1uy8NWhfwAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For a max muni pop of 786.6298666666667 we would have 7953 total units\n",
      "For a max muni pop of 7866.2986666666675 we would have 6406 total units\n",
      "For a max muni pop of 11799.448 we would have 5723 total units\n",
      "For a max muni pop of 15732.597333333335 we would have 5293 total units\n"
     ]
    }
   ],
   "source": [
    "print(\"For this 5-city code, we will break up all but the 5 most populous units. First confirm their locations and pops\")\n",
    "idx = np.argsort(muniPop)\n",
    "bigUs = list()\n",
    "for i in range(5):\n",
    "    u = idx[len(idx)-i-1]\n",
    "    bigUs.append(u)\n",
    "    for v in muniVTDlist[u]:\n",
    "        plotPoly(tractGeom[v],0.2)\n",
    "    print(u,muniPop[u],\"unit no and pop\")\n",
    "plt.show()\n",
    "threshPops  = [0.001*aDP, 0.01 * aDP, 0.015*aDP, 0.02*aDP]\n",
    "for threshPop in threshPops:\n",
    "    nTotUnits = 0\n",
    "    for u in range(nMunis):\n",
    "        if muniPop[u] < threshPop or u in bigUs:\n",
    "            nTotUnits += 1\n",
    "        else:\n",
    "            nTotUnits += len(muniVTDlist[u])\n",
    "    print(\"For a max muni pop of\",threshPop,\"we would have\",nTotUnits,\"total units\")\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fe1c7f26-7172-4c36-a6c3-964b073424d5",
   "metadata": {},
   "outputs": [],
   "source": [
    "#stop for night 1/11.  Idea from here -- check for vtd surrounds before creating units ---\n",
    "#   for any surrounds, modify munis at time of muni split, rather than later"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "b54504dc-90bd-46fb-b026-92711e346b07",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "based on above, we will keep munis <  11799.448 = 0.015  of aDP\n",
      "this yields an average of 381 units per district.  Prefer < 400 for contiguity check speed\n"
     ]
    }
   ],
   "source": [
    "threshPop = 0.015 * aDP\n",
    "print(\"based on above, we will keep munis < \",threshPop,\"=\",r3(threshPop/aDP),\" of aDP\")\n",
    "print(\"this yields an average of\",int( 5723 / nDistricts ),\"units per district.  Prefer < 400 for contiguity check speed\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "ebe6e4e0-52a1-4bd5-ac32-799ff4600522",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "now split up all but these 5 large munis and small munis.  We'll redo neighbors and onBorder later\n",
      "after splitting all but [198, 158, 106, 119, 9] and those with pop < 11799.448 we now have 5723 total units\n"
     ]
    }
   ],
   "source": [
    "print(\"now split up all but these 5 large munis and small munis.  We'll redo neighbors and onBorder later\")\n",
    "old_nMunis = nMunis\n",
    "for m in range(nMunis):\n",
    "    if m not in bigUs and muniPop[m] > threshPop:\n",
    "        for v in muniVTDlist[m][1: ] :\n",
    "            muniPop.append(tractPop[v])\n",
    "            muniCPx.append(tractCPx[v])\n",
    "            muniCPy.append(tractCPy[v])\n",
    "            muniVTDlist.append([v])\n",
    "        v = muniVTDlist[m][0]  #reassign the first vtd in the old muni as the full new muni\n",
    "        muniPop[m] = tractPop[v]\n",
    "        muniCPx[m] = tractCPx[v]\n",
    "        muniCPy[m] = tractCPy[v]\n",
    "        muniVTDlist[m] = [v]\n",
    "nMunis = len(muniPop)\n",
    "print(\"after splitting all but\",bigUs,\"and those with pop <\",threshPop,\"we now have\",nMunis,\"total units\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "6c7b5b93-3ced-4e9c-b111-2a0099a62c7c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "now redo neighbor lists\n",
      "we have assigned 8934 vtds out of state total 8941\n",
      "  remember, we skipped 7 vtds in the state list\n"
     ]
    }
   ],
   "source": [
    "print(\"now redo neighbor lists\")\n",
    "tractMuniNo = [-999]*nTracts\n",
    "for m in range(nMunis):\n",
    "    for v in muniVTDlist[m]:\n",
    "        tractMuniNo[v] = m\n",
    "print(\"we have assigned\",np.sum([len(muniVTDlist[m]) for m in range(nMunis)]),\"vtds out of state total\",len(tractPop) )\n",
    "print(\"  remember, we skipped\",len(skipList),\"vtds in the state list\")\n",
    "muniNbrSet = [set() for m in range(nMunis)]\n",
    "for m in range(nMunis):\n",
    "    for v in muniVTDlist[m]:\n",
    "        for vv in vtdNbrs[v]:\n",
    "            if vv not in muniVTDlist[m] and tractMuniNo[vv] >= 0:\n",
    "                muniNbrSet[m].add(tractMuniNo[vv])\n",
    "muniNbrs = [list(muniNbrSet[m]) for m in range(nMunis) ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "e5b3cd22-254e-4357-8630-2073ec12551f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are a total of 0 0 units with zero, one neighbors\n"
     ]
    }
   ],
   "source": [
    "nZero, nOne = 0,0\n",
    "zeroList, oneList = list(), list()\n",
    "for u in range(nMunis):\n",
    "    if len(muniNbrs[u]) == 0:\n",
    "        nZero +=1\n",
    "        zeroList.append(u)\n",
    "    if len(muniNbrs[u]) == 1:\n",
    "        nOne +=1\n",
    "        oneList.append(u)\n",
    "print(\"there are a total of\",nZero,nOne,\"units with zero, one neighbors\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "40498266-a930-4470-8555-dfd7bd9bdf99",
   "metadata": {},
   "outputs": [],
   "source": [
    "unitNbrs = [muniNbrs[m].copy() for m in range(nMunis)] #nomenclature\n",
    "nUnits = nMunis\n",
    "unitTractList = [muniVTDlist[m].copy() for m in range(nMunis)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "9ba84f5e-da22-49c0-be9d-667dde8eecaf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now let's find singles and small clusters surrounded by big units\n",
      "This is a more generalized surround operation\n",
      "checking for big surround for unit 0\n",
      "checking for big surround for unit 500\n",
      "checking for big surround for unit 1000\n",
      "checking for big surround for unit 1500\n",
      "checking for big surround for unit 2000\n",
      "checking for big surround for unit 2500\n",
      "checking for big surround for unit 3000\n",
      "checking for big surround for unit 3500\n",
      "checking for big surround for unit 4000\n",
      "checking for big surround for unit 4500\n",
      "checking for big surround for unit 5000\n",
      "checking for big surround for unit 5500\n",
      "I found a total of 13 surrounded units. nonduplicated nSurrounders = 6\n"
     ]
    }
   ],
   "source": [
    "print(\"Now let's find singles and small clusters surrounded by big units\")\n",
    "print(\"This is a more generalized surround operation\")\n",
    "surrounded, surrounders = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if u%500 == 0:\n",
    "        print(\"checking for big surround for unit\",u)\n",
    "    nbrNbrs = [len(unitNbrs[uu]) for uu in unitNbrs[u]]\n",
    "    bigNbrU = unitNbrs[u][nbrNbrs.index(np.max(nbrNbrs))]  #of the surrounded neighbors, the surrounder should have the most neighbors\n",
    "    loopNo, foundSet = 0, set(unitNbrs[u]).difference({bigNbrU})\n",
    "    while len(foundSet) < 20 and loopNo < 7:\n",
    "        loopNo +=1\n",
    "        for uu in foundSet:\n",
    "            foundSet = foundSet.union(set(unitNbrs[uu]).difference({bigNbrU}) )\n",
    "    if len(foundSet) < 20:\n",
    "        surrounded.append(u)\n",
    "        surrounders.append(bigNbrU)\n",
    "print(\"I found a total of\",len(surrounded),\"surrounded units. nonduplicated nSurrounders =\",len(set(surrounders)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "68c7baaf-a596-4c64-b32d-3e4f967b933e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "visualizing by surrounder.  Surrounded's vtds are bolded\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[] are both surrounders and surrounded\n"
     ]
    }
   ],
   "source": [
    "print(\"visualizing by surrounder.  Surrounded's vtds are bolded\")\n",
    "for u in set(surrounders):\n",
    "    for v in muniVTDlist[u]:\n",
    "        plotPoly(tractGeom[v],0.2)\n",
    "    for m in range(nMunis):\n",
    "        if m in surrounded:\n",
    "            if surrounders[surrounded.index(m)] == u:\n",
    "                for v in muniVTDlist[m]:\n",
    "                    plotPoly(tractGeom[v])\n",
    "    plt.show()\n",
    "sandwichSurrounds = list()\n",
    "for u in surrounded:\n",
    "    if u in surrounders:\n",
    "        sandwichSurrounds.append(u)\n",
    "print(sandwichSurrounds,\"are both surrounders and surrounded\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "da947a54-2aba-45da-ba57-0324912679ca",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "we will swallow all these surrounds.  Do geometries later\n",
      "now capture surrounds.  If any are both surrounders and surrounded, we handle them in second loop\n",
      "now update unitPops\n",
      "statePop, updated sum unitPops now 11799448 11799448.0\n",
      "total assigned VTDs = 8934 + 7 vs 8941\n"
     ]
    }
   ],
   "source": [
    "print(\"we will swallow all these surrounds.  Do geometries later\")\n",
    "print(\"now capture surrounds.  If any are both surrounders and surrounded, we handle them in second loop\")\n",
    "for i, u in enumerate(surrounded):\n",
    "    uu = surrounders[i]\n",
    "    if u in sandwichSurrounds:\n",
    "        print(u,\"is both a surrounder and surrounded.  Handle this one later\")\n",
    "    else:\n",
    "        unitNbrs[uu].remove(u)\n",
    "        unitNbrs[u] = list()\n",
    "        unitTractList[uu] += unitTractList[u]\n",
    "        for t in unitTractList[u]:\n",
    "            #unitGeom[uu] = unitGeom[uu].union(tractGeom[t])\n",
    "            tractUnitNo[t] = uu\n",
    "        unitTractList[u] = list()\n",
    "for u in sandwichSurrounds:\n",
    "    print(\"now working on sandwichSurround\",u)\n",
    "    uu = surrounders[surrounded.index(u)]\n",
    "    unitNbrs[uu].remove(u)\n",
    "    unitNbrs[u] = list()\n",
    "    unitTractList[uu] += unitTractList[u]\n",
    "    for t in unitTractList[u]:\n",
    "        #unitGeom[uu] = unitGeom[uu].union(tractGeom[t])\n",
    "        tractUnitNo[t] = uu\n",
    "    unitTractList[u] = list()\n",
    "print(\"now update unitPops\") # and CPs\")\n",
    "unitPop = [np.sum([tractPop[b] for b in unitTractList[u] ]) for u in range(nUnits) ]\n",
    "#unitCP = [unitGeom[u].centroid for u in range(nUnits) ]\n",
    "print(\"statePop, updated sum unitPops now\",np.sum(tractPop),np.sum(unitPop))\n",
    "print(\"total assigned VTDs =\",np.sum([len(unitTractList[u]) for u in range(nUnits)]),\"+\",len(skipList),\"vs\",nTracts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "88830fe2-0c0a-4e8e-92b0-595b8d94eafb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lets eliminate empty units, transfer their pops, update nbrs, build unit geoms, assign unit centerpoints\n",
      "state pop = 11799448 = 11799448\n",
      "Now update unit nbr lists\n",
      "Now build the geoms\n"
     ]
    }
   ],
   "source": [
    "print(\"Lets eliminate empty units, transfer their pops, update nbrs, build unit geoms, assign unit centerpoints\")\n",
    "oldPop, oldList = unitPop.copy(), [unitTractList[u].copy() for u in range(nUnits)]\n",
    "oldNbrs = [unitNbrs[u].copy() for u in range(nUnits) ]\n",
    "\n",
    "unitPop, unitGeom, unitTractList, oldUnitNo, nOldUnits = list(), list(), list(), list(), nUnits\n",
    "for u in range(nOldUnits):\n",
    "    if u not in surrounded:\n",
    "        oldUnitNo.append(u)\n",
    "        unitPop.append(np.sum([tractPop[t] for t in oldList[u] ]) )\n",
    "        unitTractList.append(oldList[u].copy())\n",
    "nUnits = len(unitPop)\n",
    "    \n",
    "tractUnitNo = [-999 for t in range(nTracts)]  #need to reset after surrounds\n",
    "for u in range(nUnits):\n",
    "    for v in unitTractList[u]:\n",
    "        tractUnitNo[v] = u\n",
    "print(\"state pop =\",np.sum(tractPop),\"=\",np.sum([np.sum([tractPop[v] for v in unitTractList[u] ]) for u in range(nUnits)]) )\n",
    "\n",
    "print(\"Now update unit nbr lists\")\n",
    "unitNbrSet = [set() for u in range(nUnits)]\n",
    "for u in range(nUnits):\n",
    "    oldU = oldUnitNo[u]\n",
    "    for oldUU in oldNbrs[oldU]:\n",
    "        if oldUU in oldUnitNo:  #this will skip the surrounds\n",
    "            newUU = oldUnitNo.index(oldUU)\n",
    "            unitNbrSet[u].add(newUU)\n",
    "unitNbrs = [list(unitNbrSet[u]) for u in range(nUnits)]\n",
    "print(\"Now build the geoms\")\n",
    "unitGeom = list()\n",
    "for u in range(nUnits):\n",
    "    geo = tractGeom[unitTractList[u][0]]\n",
    "    for v in unitTractList[u][1:] :\n",
    "        geo = geo.union(tractGeom[v])\n",
    "    unitGeom.append(geo)\n",
    "unitCP = [unitGeom[u].centroid for u in range(nUnits)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "d244db11-e615-4b99-bd0c-c716575410ee",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here is a histogram of number of vtds per unit. total no of units = 5710\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "and the number of vtds vs. unit index\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the minimum number of vtds in a unit is 1\n"
     ]
    }
   ],
   "source": [
    "print(\"here is a histogram of number of vtds per unit. total no of units =\",nUnits)\n",
    "plt.hist([len(unitTractList[u]) for u in range(nUnits)],bins = [0,1,3,10,30,300,1000] )\n",
    "plt.show()\n",
    "print(\"and the number of vtds vs. unit index\")\n",
    "plt.scatter([u for u in range(nUnits)], [len(unitTractList[u]) for u in range(nUnits)] )\n",
    "plt.show()\n",
    "print(\"the minimum number of vtds in a unit is\",np.min([len(unitTractList[u]) for u in range(nUnits)]) )\n",
    "emptyUnits = list()\n",
    "for u in range(nUnits):\n",
    "    if len(unitTractList[u]) == 0:\n",
    "        print(\"unit\",u,\"was assigned no vtds\")\n",
    "        emptyUnits.append(u)\n",
    "    if len(unitNbrs[u]) < 2:\n",
    "        print(\"unit\",u,\"has only\",len(unitNbrs),\"neighbors\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "eccac5a2-f8c1-470a-8740-e3d191a4b8f8",
   "metadata": {},
   "outputs": [],
   "source": [
    "bgNbrs = [vtdNbrs[v].copy() for v in range(nVTDs)] #nomenclature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "6feefb20-60a0-4e80-9907-75dcfe87a526",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "check - all vtd assigned?\n",
      "total assigned VTDs = 8934 + 7 vs 8941\n"
     ]
    }
   ],
   "source": [
    "print(\"check - all vtd assigned?\")\n",
    "print(\"total assigned VTDs =\",np.sum([len(unitTractList[u]) for u in range(nUnits)]),\"+\",len(skipList),\"vs\",nTracts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "1ba3f04a-9501-42b8-bf36-974502f669cd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the min and max district pops for our 15 -district map are 782696 790563\n"
     ]
    }
   ],
   "source": [
    "minDistrictPop = 0.995 * aDP\n",
    "maxDistrictPop = 2.*aDP - minDistrictPop\n",
    "print(\"the min and max district pops for our\",nDistricts,\"-district map are\",int(minDistrictPop),int(maxDistrictPop) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "89650709-3535-48dd-807f-47bbf8da391b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OK, where are the fairly big units, with pop > 0.08 aDP?\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"OK, where are the fairly big units, with pop > 0.08 aDP?\")\n",
    "plotPoly(MAP)\n",
    "for u in range(nUnits):\n",
    "    if unitPop[u] > 0.08 * aDP:\n",
    "        plotPoly(unitGeom[u])\n",
    "        plotCenter(r3(unitPop[u]/aDP),unitGeom[u])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "582dd437-e3dc-4085-834c-8e0b92c55194",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "spot check - do neighbor lists still look spatially correct?\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"spot check - do neighbor lists still look spatially correct?\")\n",
    "u = nUnits - 1234\n",
    "for v in unitTractList[u]:\n",
    "    plotPoly(tractGeom[v],2)\n",
    "for uu in unitNbrs[u]:\n",
    "    plotPoly(unitGeom[uu], 0.2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "8e1d20ee-9b51-462d-88ec-7ce534024df7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "did we create any bigUs via surround?\n"
     ]
    }
   ],
   "source": [
    "print(\"did we create any bigUs via surround?\")\n",
    "for u in range(nUnits):\n",
    "    if unitPop[u] > maxDistrictPop:\n",
    "        print(u,r3(unitPop[u]/aDP))\n",
    "        plotPoly(unitGeom[u])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "438694fa-7eb2-4628-8a32-08de211f79c2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "check for discontig units\n",
      "we found a total of 0 Units that were not queen-contiguous\n"
     ]
    }
   ],
   "source": [
    "print(\"check for discontig units\")\n",
    "isContigUnit = [False]*nUnits\n",
    "nonContigUnits = list()\n",
    "for c in range(nUnits):\n",
    "    isContigUnit[c] = isContiguous(unitTractList[c],vtdNbrs)[0]\n",
    "    if not isContigUnit[c]:\n",
    "        nonContigUnits.append(c)\n",
    "print(\"we found a total of\",len(nonContigUnits),\"Units that were not queen-contiguous\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "2f7b113b-fe6a-480b-bc2d-9ccf8a3d7a0f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "any remaining one- or zero-neighbor units? Plot them, their neighbor and county\n"
     ]
    }
   ],
   "source": [
    "print(\"any remaining one- or zero-neighbor units? Plot them, their neighbor and county\")\n",
    "for u in range(nUnits):\n",
    "    if len(unitNbrs[u]) < 2:\n",
    "        plotPoly(unitGeom[u])\n",
    "        plotCenter(u,unitGeom[u])\n",
    "        for uu in unitNbrs[u] :\n",
    "            plotPoly(unitGeom[uu],0.2)\n",
    "        plotPoly(countyGeom[countyNo[unitTractList[u][0]]] )\n",
    "        plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "ff0c9aa3-1931-4e8c-8689-05018af239f7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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pbpLdw5JM2f1hkIeWSQY/O2kYSCRxDTQxdQjohgEMv4BF03ViyoXKhh6WVHK4Yf6X4JpVcMEfoLkaHjgTHjgLNj9v575kmFBoHxDmC5/5D4pWRKn99RqC6924p30KTXdjBl3oX/23vJmLw7KsKFu2/JSNG79LZeWnmXf0QxkRrABomgEqiSEhkCGhFJIeliRoehb1sAzTISGAGC6IZkkPS6oZTpjzOTjqM7D53/D6/8DDn7XzX477Gsy5GJxDP5b/ccFgNW+tOAVNczHl+T8A4J5ShIqYRHb6yZlVQuF5k9CcRppbKjJZKLSP9eu/jr91HVMm/4AxY77U73Mppdi792Ei0QOgLBQWKBWfkmxhT0nuvk0R364UYMXfU1V8H4totFmGhNJAApYk6PEcFpUFkbLhcIKK9r5jFrJw2QXejmS6bs+SmnoWVL8NK34Hz1wPL3wfJp4KEz4BVYswS6ahG/qQF2nzeEZTVHQ8VWP+H7mjZ9Fw/3rCm5tQGuQuGU3h4nF9blPH350UnBvelFI0Nr7Otu2/pq11A253OfPnPUJBwcBmyoUjtWzafDMAbvdIezFCTUdDj89C1uO96Frn9eH2QSM3dxpFRUlMz5ek25SSgCUJHUNCKguGhFweH8oK8/y9/8e42dOYuujYdDcpJaKtfrxaI02xNPawNO+G6nfsBc0s075WZvx21/sxe6im232T+pDOn/dUEDQhYmpELXi9uYS9ES9nFe3BtMDEPtRUYCotcW11XGNfx5SGpTRMlmCZp2CGdcz3dKz3dGK8RxNbKfR5WDChlMkj8tA0GFngwed2cNSoAsaW+AblV6RpGvOO/j8AIpE2AFpKQ9zi+y13HHc3Rb0EHX/56C/c/f7dHFN+DFfPvRpDNzjvqfM4b+J5/OTEnwxKm0V6tbZuoL5hGfX1L9DW9hG67kFhsmDB0ylJrLVM+0vO0XP/j+Lioc79kiA7lSRgSUZH0q2V5JhlGhWPGg3A+pf/xvqXYeqiZ9LcotRoWPYoIwFyR6SnARuegqeugmig+3ZNjxemM+xr/eP3DfuiGbwcPJbfNS1gkrMBl2bi1Cz2Ruzp2s1hcGoKQwdDU7h0MDTQNfva0LX4NeiahqFr6Bo44tt13bIfUxEcrfuwvMUEqk5l7d5W3t6+i3DMoi3cmSR4dFUhF84bzUXzRuF1Dc7bgKsyl9G3n8Qopfji9hCjckcddv93a97l9nduB2DZ7mUs270s8dikwkmD0kaRPsHgHj7aeCNNTStwOAooKlrI5MnfY/++x6ip/QcOR0FKnqcjOVZLx9pZGVAdNqXS3FskAUsSOnNYMv+Fd/xFJ3PUKXP50zevxcqCACtZKmp/S6q4+JtD/+QfPAp//4pdE+X839tTkjuCkT4MU6h3dsPf1/HSjy8bxMYeWsy0g5Y3tjbw9zV7ueWfG7hz2RZu/tQMzpkzeMmMmqZxzsRzDt82K8blz18OwGenfJbjRx3PG3vf4OXdL9MYauS4SqmOO1wopaip/QebNv0QpyOfo476PaUlixOF32pq/gGAZUUwjIFXie0IWHQtTR93mf+xkaT09xZJwJIEXbcTBLMhYAHIK8knp2AUkUBbupuSQvE8Bn2IkzU3/suuVjnjPLjofjv5tZ86YhulVFryMRyGTqHXxadmV/Kp2ZVUNwa47d8fce1f38NpaCydNTJlz6WU4u0djSzfXE+u28HXTpl42J/ZoTv45vxv8j+r/4dHNz/Ko5sfBWB68XQaQ420hFtS1jaRPpFIAxs3/YD6+heoKD+PqVNvxeHI67ZPR2BhWaGUBCxWPKdPS0vAMsx6WNJMApYkaFlUh6WTnjUBVlLSkXj5wWPw9y/D2BPh7F8NKFgBO10P7B8lE/JHxxR7ues/5nH5n1Zx7V/f45Er3cwfWzzg85qW4tq/ruFf62oS2xrbI3z/7OmH/f/70qwv8dmpn2VT0ya++O8vAnAgdICfnvhTFo5cOOB2ifSqrfsXmzb9EICjZt3FiBFLe9yvY+jGNEM4nQMfFlJWuoeERKpIwJKMRA5L9gQA2rAbO40Hi4P9BmDG4N3/hdd/aVelnXoWXPxwSp83k/5XNE3jvi8ew6LbXuaWf37I/Zcdw4j8ga1y2xqK8q91NbgMnY0/XsqfV+zk1qc/pLE9wg/PmUGh13XIY71OL0ePOJp1l60jakVxpuNDRqTc5i0/obr6AUpLTmX69NtwuQ69LIOh26+/N986Ib7lUH979vpldg9NT/vYj1tWx5BQOl5LMksolSRgSYKWmNacPT0swy9g6RgSGoRah0rBjuXw6u2we4W9beaFMP4kmHVR6oKVLkNCmTAe3MFp6Nz7hflc9dBqzvzN6/zovFmcdVRFv3uzCr0uRuS5qWsNo4DLTxhPjtPgv//1Ee/tbuKhLy9kdJG393ZJsJL1QqF9vPnWSQDk5k5j9ux7e11NefToy2hv34pphSFRF0WReD+L10IxzXba2jZSXn4ObldZt3OoLvsCOBx5eL3jU/mjJWe4vQ+nmQQsSUgMCWVgVdFD0rThNSQ0GH/0216B9x+x65k07bBXRj77V1A0FiYuTnlvTsfZMvF/Zf7YIv513Unc+MQ6rn54DXNGF3DNqZNZPG0Eut6330NLMEpda5iTp5RhxI+9eEEVx08s5dL7V/KlB1bxg0/NIN/jYHt9O1vr23jqvb3MrMxnWkU+k8tzOWXKCAq8ErBkm2i0hQMHXqWx6S32738cAMPIpWrM/2P8+K8nFQR7PBXMmXNfr/u1tKzl3dUXUVn5OfJypw247YNmWL0Pp9eAvq7efvvtaJrGN77xjcS2P/zhD5xyyink5+ejaRrNzc29nueWW25B07Rul2nTMucF2FE4zsqigEUbZl2RSimUSlEAEQ3Co5fB/50PNR/Y6/Nc+gR85RU49gqYtGRQhp50rTOHJROV5rr542XH8PBXFuIwdL7y4Lss+dVynlu/n5iZ3Gt/Y42fz//xbQxd47tndf8brirx8sCXjsWha1z2v+9wwe/f4puPvc8/1+6jIMfJa5sbeGx1Ndc9spbzf/8moejwmeU2nCllUt+wjLVrL+f1Nxaw4cMbaG3dgMORz7hx13DiCW8xYcJ1g5B/Fu91zaDeyoNJD0sq9buHZdWqVdx7773Mnj272/ZAIMDSpUtZunQpN910U9LnmzlzJi+99FJnwxwZ1PnTOb0jve3oC03r7BYdFhQqFW9NsTA89GnYt8ae9ZPKIZ9e6IklqTL7/+X4iaUcf1Upz3ywjwfe3Ml/PrSG8nw3F84bzTFjizhqdAEj8jrzXExLsbHGz1Pv7eWBN3dSVeLl0a8ex7SK/IPOPWlEHv++7iQ21rSiaVCe56HI1z2n5c5lW/jVi5upaQkxrnRwCtyJ1GhoeJnNW35CMLiL/Py5TJn8A0rLluBxV6S7aZlBkm5Tql9RQVtbG5deein33XcfP/lJ9+qTHb0tr776at8a4nBQUZGZL/LEkFCa29EXmqYRDR7gj9d9396gFJVTZ3DW1Zemt2H9pCk7YBmwHa/Drjfgi/+ACacM/Hx9kOk9LB/XMf35w31+Hnp7F39bVc3dr25LPD6qMAeHobGvOUjUVHhdBt9YMpmvnDwBt+PQ0881TWP6SDuYUUrxr3X7+dpf1nDJgjEcO66YX724mQmlPkYVpX9tpExh9zDC9oY23tp2gLXVzexrDuJxGlgKPjN/NCeMBwcN5OUdNeiz6UKhfWze8mPq61+guPgkZs78NQX5cwb1OQ/W8YeUyUHB8OrpTrd+BSxXX301Z599NkuWLDkoYOmvLVu2UFlZicfjYdGiRdx2221UVVX1uG84HCYc7lxTxu/3p6QNh9K5WnP2DAlNWrCQ91+oJdzeDECodSdtjbuzNmBJWaLqgS12FdpxJw38XH3UEbA8vmYPHoeOpZRdjl8pLEthWorRRTmcPjOzAvcZlfn89IKj+O/zZ7GnKcia3U28sKEWt1OnNNfNmKIcJo3IY97YwkSg0hqK8trmBva3BPnktBGEoia/eH4Tr26qB6Aszz4uEDHZWNMKwF/fqeav71QDcM6cSpzGkb2YfDBi8l51E8+tr+HBFbsS252GxoyR+VSV+Fizq4m9zUFe21yP2zD54oyHOGV8DSPKllJcfCJe73g8nkp7deHDsKwIweAeIpEGTLM9XrTNQ05OFR7PGHTdgWXFaG3bwL69j7C/5kmczkJmzfwNI0acnZa6QtnQg7zbbOc5rQX++QU09PgaRfHUBzR0res2+3YiNYKP3Y+vbdRxX9cMdHR0TUfXNYz4ffvYg4fKEs/TcT/+f9Z1347fqMIOkFXit6xAtTLfilA46L+1Q+tzwPLII4+wZs0aVq1albJGLFy4kD/96U9MnTqV/fv3c+utt3LSSSexfv168vLyDtr/tttu49Zbb03Z8/cmmyrddjjxs2dw4mfPSNx/+Ob/oW77+4c9RtmvUPsFquIv1M5XcHwlUxLbu/0+uh7X5Rj7SnUsdNr5PF0fj5+w2+NdT60U0VBnWfl+i4Xho6chf5RdpXaIjSywh1F+8NT6btvtsvtaYqho60/PGvK2JcO0FP5Q1E6MHZEXD7gUZvz6gz0t1PnDrNndxOOr99AStAt2/eTZjwCYWGYP75w5q4JpFfms3H6Aklw33zt7Oo+v3sM/1u5LPNfjq/dw/QIvrLzbzisqnjD0P/AQ298S5NkP9vPuziaqmwJsrGnF7FJKYcbIfG48cxrzxxbhc3d/665uDHDub//FppZFXFTSRE3tP9ldfT8AmuYiJ2cMXu84vDnjyPGOw7LCBAO7CAR3EgjsJBTaC/T8hUzTnOTkVBGJ1BGLteJylTFxwg2MGnXJQUXfhlTHG0YGD7s8rgf4s89J4YH34vOcOuc79XQBDQVYWtdtnbetdP6seTqXR/dzQ/pa0LeApbq6muuuu44XX3wRj2dgtRq6OvPMMxO3Z8+ezcKFCxk7diyPPvooV1xxxUH733TTTdxwQ+evze/3M2bMmJS15+MSix9mUcDycbqmYZkWd3/tlZ4Dkgx3lPcAo/P6+ccaCcDT18H6J+zFCI/7Wmobl6RjxhWz6SdLUaozSOk6A+fRd6v59uMfYFoqMbsmU9S1hrj43pVsb2jvdd9RhTmcP7eSL580gZN+/kpi+31fmM+EEZ0fcNcxOXH7xQ9rAfjReTO5+R8bGF/qs1eh3vICrLgLvrkR8jKr56k/lFK8uqme4yeVoBSs2dXEK5vqeHVTPVvq7MrUmgbnzK7kPxZWMX9sEVNG5PU6U2tMsZciT4Bcj5dpU69n6pRbCAarCcYDkkBwJ8HATuobXiQU2oumGeTkjMWbM44RI85IBDJuVzkORy667sI0AwQCO2gPbCcQ2I7LWUJR0XHk589Bz6Ap55mcdGuVTqUqVMPTFzw9sBMpe3p3x7VSFpYVw1IWlhWNX8fvY3X7spjoI4mPEHQETonzdtkv0dsS7wGye3jsbZ958QoiI2eTTn0KWFavXk1dXR3z5s1LbDNNk9dee43f/e53hMNhDGPg31wLCwuZMmUKW7du7fFxt9uN2z3wks3JysppzR9TVpVP034nJ352sv2FpKM7MP63nujSTdy379j7xjd3ie47t2tdjul+zoMfp7NLsst7jGb/RSS2J47p8rx5W97HeK8fry2l4Nkb7J6V034EY4+HUfN6P26QHC63w2nYv5SoaWGkoQfoUJRSfPfv6/CHojz85YW4nQaGruHQNXRNw2FoieGughwnZXmdf5tfG7mJ3++fyir3f1L2ez/MOB+W3g753ZcBuPXcmdz8qRk4DJ3jJpQwIs8NO/7DDlhQ8Ltj4T/fsKecZ7HxN/0rcdvQNUxLMSLPzSlTy7h28WQ+MaWMgpz+BQPhmI7bYX+50jQdr3csXu9YSko+0W0/y4qiaUav9VCczkI8nkqKi0847H7p0jkklLkBS8qGyjTNHsruuAsY8ctQyXMXpL03q08By+LFi1m3bl23bZdffjnTpk3jO9/5TkqCFbCTerdt28YXvvCFlJxvwBLJklnSHdEDZ44Dl8fBUaeMTndT+qfJk/wfy64V8Mp/Q6QNGndAqBkuvA9mf3ZQmzhQHTkbT7+/D5dDT4whW1bPHWFdfxsf/9X09KvqNoLXfTSvy3Z10PatdW289FEdd3xuLsdPOnSF0p58e9w2vt3UZfj2w6fsy/wvwVn/A4Yj3l4Nx9u/AzPKFE2Dl26x36DP+z3842sQ9sMfF9szuyZ8oodnylxKKV7b0sAfX9/ebfv3z57OwvElTB+Zl5IPNtMCp9H7W3om9Y6kRuYGLJAduTbZok8BS15eHrNmzeq2zefzUVJSktheU1NDTU1Nondk3bp15OXlUVVVRXGxvU7J4sWLueCCC7jmmmsA+Na3vsU555zD2LFj2bdvHz/84Q8xDINLLrlkwD9gKtg9AFpWVbr9OLsaQBb/4SgFvXwjBCDQCM98Aw5sgzkXw7SzYfSxQz4jqD9GFnjQNPivxz9Id1MOkuM0OG5CSfIHKAXblsHONzu3/eAA1H1o95q8epv9f7ToGigYDa/9HD78R+e+JZPtBOl/xIfvyqZD7gh48Dw4+b/gE98e8NpOg00pxbPr9vOrFzazvaGd6SPzufOSozn7qJGDMuRnKg3jSEpUjr8fh8P7yckZja4fesmHdMnk4apslPJiJ/fcc0+3hNiTTz4ZgAceeIAvfelLAGzbto2GhobEPnv27OGSSy7hwIEDlJWVceKJJ7Jy5UrKyrqXW04nDS2r1hI6iJbt0+sOs2KgZcHe1fD+w3blWmXBOXfA0Z8f0hYO1PyxxXx461JMpdC1zllFutYxjmzr3iPSsU0dtK0nnSN/Wg/buu6nHbTtsHkUbfXw3I2w83XwlUHIDy27oXQKnPxtOOVGO9F55Oz4ZS4suxX++rn4ybsEH9eugZKJ0H4ANj4DhsteJiFvJLz+KzvY2fRvOOc3MHr+oduUJh/t9/Pgil2s3tXI5lo7L+V3/2EHKoM5m8ZSGsYR9PmoG3Ye5Xtrv0hB/tEcc8zjaW5RD7Ts7pnPNAMOWD5eb+WWW27hlltuOewxO3fu7Hb/kUceGWgzBp1SFq89+y9W7/HHPzEsu8teEU9g7ZjlorrMlFE9PN7xAlaJF3LnrJiD9+maGXvQfl0Spjpvd2zvnGmjlMLat5W2pgBf/vO7TCnP7cw+7zY00H32zomTSzlpcoYEjR+f1hxuhS0v2t/Wd7wG/r2QWw4nXAfHfhl8fRu6yBQ5rszJXUnairvg+e923m+r7bx9wT0wqoegYvISmLQY6jdBe729LII7t/s+vhKYf1n3bZ/4L/vYp6+DP54Kx/w/OO3HBx+bSv79sPpPfNDs4he7JtPuKiFiWrgMHZdDx2nYl/ZwjH0tQaobgwB8avZIbjlnJosmlgzJtF9LdeYSHQny82Yz+6i72bPnIQLBneluziFldc92hsmgcrKZrclZSNH+HUT27+jxcTtE0Lrc75pV+rH78alrndmodL/fcbzWfX+t63kPKmbX5Vit+3OBPWFxn6eSlz6qZVOtP/EN+1Dfruv8Id6rbs6cgAUFkVZ7JWVPIbzwA/DvgfJZMP1cmH4OjFmYyIkQQ6h0qn09ZiGMmN65ffWf7KCyp4AF7BffiGlAH5fhqDwavvwyvPA9ePse+zVRNg0+/3coGNWfn+BgkXZY95g9TLXtFUDxZuwcXo9N4/y5XrxuB+GoRcyyiJoWkZiiPN/D7NEFzBpVkJa1kCylcySNCLX41/DBuqsA8Pkm97J3egy3IaF09xbJu3uS/lZ1CTedOY0vLBqLHp/2petaWgomDYUbHl1LdWMg3c3o5IsHTs/cAChweu21f9I440fETV4Ct7QcvL36HQg2Dc5zGg4482dw3FVw94lQvxF+PcNeB2r6ORxYG+PA/Q8w+dVX0Fx9yG2o3wzv3g9r/2on+o4/Gc76Bcy8EPcT/8DzYYQ7Lj56cH6mAbKUlnHT4QdTNNoMwNFzHyQvb2Z6G3MIGsNtEdr0koAlSZquYxgGzkxa42gQaWhkVMrOnIvtXhTdaQ8HOVzgTmPRKtE7Vy6E2wb3OYrGwXf32DPD9rxj94Y8/Q3qHrGnTYde+BM5Z11x+EKBrTX20OL6v8P2V8Bbaherm/+lbtOoPS4XYRwopTLyi4odsBw5XSxK2cUk8/Jm4HQWprcxhzFchoQyobfoyPj0TQGN9HeHDSU9E5PFXPGF8Bx9mK0i0sfls4fxhsLYRfblhOugfhOjfT/F3PMROe/+F2z5LUw9E8YssJN5HR47SNm9Ara9DHtW2TPQqhbB+ffArAvBcXCdJ7fLhUInEonidmfejBR7SCgLc6D6qXPWZub+zJkY2GYzCViSpGkMkzg5ObqWYT0sIvu4c+1ckKFWNpW8//qznai98VnY/BxseR7eubf7fjnFdiHB8++xh5JyD5+v5YkHKaFAK2535gXNptJwpKgWVjbo6GHpbZ2kdMqEXonhRAKWJB1pLzxdz8AeFpFdXHn2dOd00TSY/in7AnaNnqadYMXsxO2SSfYLPUketwcwCQfboCizAhalFDHLgcs4cv5mlTIB0LTM/hiT99HUyez/6QxzZL3upIdFDJDLZ1cbzhTeYvvSTzk5HqCdQHsaeo16ETOjWMrg5c2tFHmfRdOJr9xLfGVf+wuXoevkefM5deaCXtcnSiV/63raWj/E5SqLLwmg26sPa0a32/Z9rYfbOprm6NyuGcRi9nBjb0sMiOFDApYkHXlDQsMnWUykiTs3swKWAfJ5c4B22oOZF7Bomk6+q401+wpZk1j0+lCVuRt44qt7mT9+6JbpWLXqvEE5r6Y5M3tISNOG1ftoun8WCViSdOQl3Wpk8VqPIhO4fIM/S2gI+XJ8QAOBQDDdTTmIw3Cw6gfnE4wE7UKRll2s0lImlqUAC1PB2u3vcPXjDqJmZEjbN3Hit9m27edUVFzAxInfiq84bMYvFnYhTvu2wkysSKyIP57Yt8sFE7erPON7WNL9IT+cSMCSpCMt21vXwDqCAjQxCFx5w6qHxeuzZ6m1B0NpbknP3E43bufhV7HfXZsLhIa8wFxF+Tls2/Zz3K4yPO6KoX3yNDrSch8HW2aHphnE7mFJdyuGjqZpR9TPKwaBOxdiITBj6W5JSvh8dvn/YDDzeliSZVoduSxD+7xu90hyc6fR2Phm7zsPI/b7qLyRpooELMk6wnI6tCPs5xWDoKNuzjDpZfF47UKFgfDQDqekUqwjYNGG9m9b0zTKys6gtW0Dy16eiGVFh/T502m4vI9mQm+RDAklKf3/VUNL6rCIAXPFKxE/+kW7KrHhBMMdv3bZxdk6bnfdbjjjj7m6HOOyy/Frun1B67ytGx+7bXTZZthTlzWj++MdeQ+aFj9X17W/Pr7Nvu2I/z2Y0fDQ/P4GgRnPS3OkoYT/uLFXsWfPQ0SjB3jl1Wmc+smtw36oPRM+5IcTCVj64Ejq2ZMcFjFgo+bBnEvspRRiYfvajIIZBjMSvx2BWCR+v8vFyrxhJHuS7UNEVWZ2TIeiJsGIiRlPujWVwrQUlkXi9p74kk/h0A78rQE7uRUVv7biK813JMFa2CvDH+q+ih/T5dhD3refY/y4r7F5y48BiETqcLvL0/PLGiIaR9j00kEmAUuS7OlpRw7JYRED5i2GC+7p37GWBVbUDnQ6AhszAvEPPpSKX+wZJCgLLNO+bcW3ddzv6TGl4ueKX8PHttHjbcdfNcyRh1h9Oo3q/CFO/PkrRGLJTe3bufWbNFUP0bIJaPGZPFq3GT2ZXvBNHCzd+TjyikmSqRS1wQjVraFET3Hi/Q2VSMpVdP6nqq7b7B0TQY+lOsc2rS7HKVTne3H8MQuFpRSmsisrmPEpi3PK8ih0D84S9lomriUkjhy6Drq7xzV90snx6HPE9MxbR6iuNUwkZvG9s6YzrtSHodvDuoauYcRXljd0DR1wa3upKvq/bgXcOoMJPT5Mo3e/r+lo6PFr7WPHcvD+3c57BA+LSC5gSknAkiT/3GLudoe5+92N6W5Kwsj18N7SuYNybstSQ1oJU4hs4NA1YhlYoCgUtcvUnzK1jMnlva1i3v9qv6JvNIZX4bh0k4AlSaWlOZRrBovcHpTqIUcvnlylddmmiE/D0uztHXt0HKvRWd9Fix/TkaSla53n0jXQsb8paYChwY931dA6iH8HMUulJTFPiEzmMDRiGZiNHowHLB5n5lZ9FWKgJGBJksPQOXFEAd+bWJnupgBwb3U9+wZxobOYqXD0YWE4IY4Ehq4TMzMvYAlF7V4fCVgyi4bUYUklCViSpCCxgFgmqHYBaGyvb8Np6Oi6hkPvHLM2jI/d1/s2lhyzFA4jc35eITKBPSSUeR9AoUQPi3zJyCTDaS2hTMhFkoAlSZZSGTWjflJUY6tTcfz6rQfPt+7p70PXKAlabDhrXlLnNy0LQ4aEhOjGYWiYQ5jDYlqKutbelwKo9dv7SA+LGEzpDr4kYOmDTPr4fvj4qfxlRx0xSxFT9swiq6PuglJYii71GODvfj/NfegxiZkKpwwJCdGNQ9eGdEjoJ89+yANv7kxqX5/LwDnUNffFYUnhuNSSgCVJFt0TbdOtKtfDTUdVJb1/9UvrWRVLvkJnzFLSwyLExzgMfUiHhGr9IWaNyudbp0/tdd+RBTlD0CLRF7KWUGpJwJIkpeyZOtmqo+XhmGnXZ4jXZjgUU3JYhDiI3cMydENC4ahFRX4Op0wdMWTPKUSmkoAlSRaZlcPSV4ahYUYUU7//XPftumZPm44n5uqafT8YNTl5clmaWitEZjKGOOk2HLMo8A5OcUgxNNKd9zGcSMCSJHuWULpb0X+zKgv4qMbkx5+dk8hzMS3i+S4duS8k1iCxlOLESaXpbrYQGcVh6JhDGrCYuDOs2q9InhSOSy0JWJJkqcxKuu0rl0PH63Jw4bzR6W6KEFnLoWtEU5B0G4qaNLTZOWUdKQ4qvlxH1yU+djS0M2lEb5VrhTgySMDSB9me8Z3drRci/ZyGRiQFOSwX/2Ela6ubk9q3UIaEspaqD9MSbmHhA8d2396l10UdtE0R1qOJx92WK/HZY1dMT9RMR1Ndbice6/y362dW4r46eP+u59bQwFKd5zY0LBT1RiMzmTLwX8oASMByhJBOSSEGbkSehxp/73VRelPnD3H+3Eoumj86vpigvb1jlY+ObRpw1OiCAT+fSI/TOIlgbR2u6UVA92ADus48jd+PBwn1ZgPL299iae6p+HQv0KUHLrGcbpd7qvM2iUV0OxbhjV8rq9u+HY8l9lOJZXqxQlGi9QEc5T40l73gpVkTZGneqYP0m0qOBCx9kM1jkQrpYRFioIp9LjbXtg74POGYxeTyPE6SxPZhrdhRxIWB0xl1zvF9PvbGQWjPQNTeuQaXkZ/WNkiVoSQNhw/7TKojI0Q2ynU7aA3FBnyeUNTE7ZC33yNC9n7PzTjyF9MH2fy6y+a2C5Epcj0O2sIDD1jCMQu3lNEf/uRLYkpJwJKkbO+dsJTCkL8eIQYk120HLAOpXhozLWKWkh6WI4GmybfFFJIclj7I5tedRXbXkREiE+S6HZiW4sYn1jEi333Q6ui61mWVdF23t8VXUu+47qjjIgHLEUJK86eMBCxHCEsp9GzvJhIizaaPzGdkgYe/vVvNyAIPStnrbpmWhWnZBRhj8cKMMUsd9rOqIt8zdA0X6SFvuSklAUuSsv11ZykZ/xNioKZW5LHipsVJ799RObprMGNaCkPTpOT+EUBDOlhSaUCfYbfffjuapvGNb3wjse0Pf/gDp5xyCvn5+WiaRnNzc1Lnuuuuuxg3bhwej4eFCxfyzjvvDKRpgyKbX3gyJCTE0NN1Daeh43Ea+NwOCnKcFPtcEqwcKTSN7E4myCz9DlhWrVrFvffey+zZs7ttDwQCLF26lO9+97tJn+tvf/sbN9xwAz/84Q9Zs2YNc+bM4YwzzqCurq6/zUu5bP+st5TK6tWmhRAi60i8klL9Clja2tq49NJLue+++ygqKur22De+8Q1uvPFGjjvuuKTP96tf/YqvfOUrXH755cyYMYN77rkHr9fL//7v//aneYMmm193iuyf6SSEEOLI1a+A5eqrr+bss89myZIlA25AJBJh9erV3c6l6zpLlixhxYoVPR4TDofx+/3dLoMt29cRshQyrVkIIYaSpmV3LkGG6XPS7SOPPMKaNWtYtWpVShrQ0NCAaZqUl5d3215eXs7GjRt7POa2227j1ltvTcnzJ2vMnl1YH73Hy/lee60GpQ56ISq69MIoRc6HG9BCIdqPnk+isL+l4ms9xI+I39biS7R2rAVBxxG6jkJD6TpKO/gaTbPvazpK10DTCYweQ7hiZOfaEsCH7UHJYRFCiBRRShGrD6KiXRbD7HiPjXdnm/5wdnfNZ5g+BSzV1dVcd911vPjii3g86ZuSd9NNN3HDDTck7vv9fsaMGTOoz3njb2+nuKG+X8cWP/PPFLfm8LaOGcfXv/+zxOJpYF9fWF50uMOEEEIkKVLdSv3v3+91P80tFY1TpU8By+rVq6mrq2PevHmJbaZp8tprr/G73/2OcDiMYfTtP6e0tBTDMKitre22vba2loqKih6PcbvduN3uPj3PQJWh8Fx6KXlf+xqarqNpHattdi7N3REddCzdrcJhNKXQczygaWha/BEtPsCkxVdk1ToX+db0+ChdR1diR2+OZYFldd5WChW/xrIStw/84T6mL1/Ojk90T4YWQgiROipkAlDyhekYBfHPoy69KR3VkI1c11A3bfCkeXirTwHL4sWLWbduXbdtl19+OdOmTeM73/lOn4MVAJfLxfz581m2bBnnn38+AJZlsWzZMq655po+n2+waE4nnvw8ikqK+3BUXmqeuw/7GsVFqHA4Jc8rhBDi8Jyj83AUDO0X6LRJ88yNPgUseXl5zJo1q9s2n89HSUlJYntNTQ01NTVs3boVgHXr1pGXl0dVVRXFxfaH/eLFi7ngggsSAckNN9zAZZddxjHHHMOCBQu44447aG9v5/LLLx/wD5gyWVIBSHe7sSKRdDdDCCGGtY4elCMmNTADPv5SXun2nnvu6ZYQe/LJJwPwwAMP8KUvfQmAbdu20dDQkNjnc5/7HPX19dx8883U1NQwd+5cnnvuuYMScdNJ0/SM+A/rjeZyoyRgEUKIwdXxeXDERCzpN+CA5dVXX+12/5ZbbuGWW2457DE7d+48aNs111yTUUNAB9F1O3ckw2kuFyocRimVyK8RQggxWFLzPtu4p54dD76LbnaeryNDMrGl0sOcKz6RkufrlzR/pMhaQsnKkhLLmtttB1axGDil/LcQQgyKjhSBFH2IH/hwH+X+XJryQmBodCl+AShcbRra9iO791wCliRpmmbPxMlwutvOSG9/+x10tyteLwZQFo7yctzjx6e3gUIIMRzE45XWLQ3oXoe9WJsen/Wp63ZZVk1DM+wZouj2bTQNTbcv6BqmZWE4dFTEnnU07soF5JUVHPR0a3//Mu69JpZloetH5lK2ErAkS9ftom8ZziguAaD6y18++LHCQqas7Ll6sBBCiOQ1tDaiAW2PbkvJ+bzxa8N5iNm2mkae6WHfd99MbOpaHLQ71cOt3qnD9BYZSqO90CSd1bwkYEmWrmfFLCHvwgVMfPEFVDQK2JXjNF2n5Z9Pc+C++9LdPCGEGBbaC0z+6X6d0z65hBx3TrwWFvbFivdsWySqm3fb3uV2zf79OB0uSoqKcRXm4C3M7fH5xp8/h71vbUEp0JQ9S0l1+UzqWn3dvlKdH1lKddnWUVU9fq1U99s9PA6KmppafLmlTBiMX2aSJGBJlgaozB8S0jQNVw9Vfx2lJVkxpCWEENlAKUVAizDl2Jn4fL5+n2d6kvsVjCym4KKF/X6egbrnnnsY40nvl/YjcyCsHzRNR2XBkNAh6UZWzHISQohsIrMxh44ELMnKkiGhQ9K1ztL+QgghRJaRgCVZmpbVPRSaHk/kyuKfQQghxJFLApZk6RoqC3JYDsmI/1ebZnrbIYQQQvSDBCxJskvzZ+dwir3Cczx7XHpYhBBiwGR4fejJLKFk6TqYmf9hH1y3nuqrrkIFAijTRMVi3XtVJEFMCCEGLLH4obynDhkJWJKVJS/KyO5dmA0NlF1/PbrXi+Z0oDkc4HDgrBiJ7j5ClkEXQoghIAHL0JGAZZgq/vyl6AOoDSCEEOLQZEho6EkOixBCCNFHMiQ09CRgGWbkj0cIIYaOvOcOHQlYhinprRRCiMFzJA4JpftnloBFCCGE6KcjpYclE35OCViGmwx4UQkhxHAnOSxDT2YJJSkSriXwwocc+ODZzo0dL9Sur9eP95j11oWmDnG7pw0fu+s4ajzTbnvi8OcXQgiRch0By1/+8hc0TUsELoe7faht06ZN46ijjhrS9mcjCViSFDhVR/vAictZ3CVwUPZtRfeg5aCAWzv03X7uG9u0i9jyjw7T4iNvfFUIIYbK2LFjmT17NqZpopRKBDBdrz9+6enxhoYGWlpaJGBJggQsSWo8ahfehROYe9yL6W4KAJtvvZTI82sPfkC6J4UQYtAVFRVx4YUXDvg8zz//PJs3b05Bi4Y/yWHpg0Bge7qb0IWG9KIIIUT2kzyY5EgPS5Ly8+eQ65ua7mZ0oaG3Kqq/dnVnnoxSxOrqEreFEEJkNsuy0HXpO0iGBCxJy6wI2Di2isBHa+2FDRPJvxqOigoKZx+Fnpub1vYJIYTonQQsyZOAJUvp00fivzqHuSfdk+6mCCGE6CcJWJInv6WkZdYQi6bpZFqbhBBC9I0ELMmTHpZkKZVhM3AyqS1CCCH6w7Is9uzZw3333Yeu62iahq7r6LrO9OnTOfbYY9PdRGKxGK2treluhgQs2UtDKSvdjRBCCDEA8+bNw+FwoJTCsqzEZffu3WzYsGFIAhbTNIlGo3g8nsS2YDDIhg0b+PDDD9m5cyeWZZGXlzfobTkcCViSpA6qDpde9jQ4GRISQohsNnbsWMaOHXvQ9kceeYRYLDZoz9vS0sI777zD3r172bt3L9FolKOOOoqTTz6Z6upqXnjhBcLhMGPHjuX0009nzJgxVFZWDlp7kiEBS9IyLTiQgEUIIYarWCyGwzE4H9FbtmzhiSeeQNM0xo4dyyc/+Uk0TeONN95g3bp1AMyZM4clS5akvVelKwlY+kDLoB4WpIdFCCGGrebmZlpaWvjNb36TyGkxDCNxu6dtRx99NNOmTTvkOZVSfPDBB/zjH/9g4sSJXHjhheTk5CQenzdvHrt27aKgoIDy8vKh+DH7RAKWpGVWcKChJ9akEEIIMbzEYjEsy6K9vb3XNYk67Ny5k8997nM9BjWxWIzXX3+djRs3MmfOHM4991wMw+j2nG63mylTpgzdD9lHErAkS5GBs4QkYBFCiOHI7XYzefJkzj777KT2/+Uvf0lbWxsPPvjgYfe74IILmDNnTiqaOOQkYEmSnXSbQXPlZUhICCGGrWg0itPpTHr/yy67jG3bth0028iyLJRSBINBVq1axXPPPcfUqVO7zQjKFhKwJM3KqBwWTaY1CyFE1lu5ciV1dXVomtbt0tbWhsvlSvo8ZWVllJWVHXafUCjEunXrePDBB7nssstwu90Dbf6QkoAlWUpl0qxmZEhICCGy37Jly/B6vfh8vm55KkVFRYwZMyalz3XRRRdx/PHH88ADD/DYY49xySWXHJTHkskGNMZx++23o2ka3/jGNxLbQqEQV199NSUlJeTm5nLRRRdRW1t72PN86UtfOii6XLp06UCalnIyJCSEECKVLMsiGo1y8sknc+WVV/LVr36V//zP/+Sqq67iqquuYuLEiSl/zpEjR3LxxRezdetWfvaznxEIBFL+HIOl35/Aq1at4t5772X27Nndtl9//fU8/fTTPPbYYyxfvpx9+/Zx4YUX9nq+pUuXsn///sTlr3/9a3+bNkhURg0J2ZVu090GIYQQ/RWNRgH6NPSTChMmTOCKK64gEomwevXqIX3ugehXwNLW1sall17KfffdR1FRUWJ7S0sL999/P7/61a849dRTmT9/Pg888ABvvfUWK1euPOw53W43FRUViUvX82YClXFrCWVcc4QQQvRBJBIBhj5gARgzZgwzZ87ko48+GvLn7q9+BSxXX301Z599NkuWLOm2ffXq1USj0W7bp02bRlVVFStWrDjsOV999VVGjBjB1KlTueqqqzhw4MAh9w2Hw/j9/m6XwWehZdKQkBBCiKyWzoAFYNy4cezbt489e/ak5fn7qs+fwI888ghr1qzhtttuO+ixmpoaXC4XhYWF3baXl5dTU1NzyHMuXbqUBx98kGXLlvGzn/2M5cuXc+aZZ2KaZo/733bbbRQUFCQuqU5M6olSMTRNcpSFEEKkRrqGhDrMnDkTgD/+8Y+H/LzNJH0KWKqrq7nuuuv4y1/+ktI53BdffDHnnnsuRx11FOeffz7PPPMMq1at4tVXX+1x/5tuuomWlpbEpbq6OmVtORRlxdB0CViEEEKkRkcPS1/qraSS1+vl/PPPB+Chhx4iHA6npR3J6lPAsnr1aurq6hLLYTscDpYvX86dd96Jw+GgvLycSCRCc3Nzt+Nqa2upqKhI+nkmTJhAaWkpW7du7fFxt9tNfn5+t8tgU8qUHhYhhBApsWfPHt555x0gfQELwNy5c7nsssuorq7uNdc03fr0Cbx48eLESo4dLr/8cqZNm8Z3vvMdxowZg9PpZNmyZVx00UUAbNq0id27d7No0aKkn2fPnj0cOHCAkSNH9qV5g8pSMTQte+arCyGEyFwPPfQQoVCIgoICfD5fWtsybtw4fD5fxk9x7lPAkpeXx6xZs7pt8/l8lJSUJLZfccUV3HDDDRQXF5Ofn8+1117LokWLOO644xLHTJs2jdtuu40LLriAtrY2br31Vi666CIqKirYtm0b3/72t5k0aRJnnHFGCn7EVFGSdCuEEGLALMsiFApxzjnnMH/+/HQ3h3fffZeWlhZmzJiR7qYcVsrHOH7961+j6zoXXXQR4XCYM844g9///vfd9tm0aRMtLS0AGIbBBx98wJ///Geam5uprKzk9NNP58c//nGGlQ1WZFipWyGEEFkoFosB6R0K6tDU1MSLL77IvHnzGDt2bLqbc1gDDlg+nhjr8Xi46667uOuuuw55TNflsHNycnj++ecH2oxBl4l1WIQQQmSfjmTburo69u7di2EY6LqOYRiJi9PpHJIFCletWoXD4eD0008f9OcaKMkiTVqmVboVQgiRjRwO+6P3jTfe4I033uhxH03T+OpXv9qnCSv9EQqFKCwszIrVmyVgSZqVYT0sUpdfCCGykcfj4Zvf/CaBQADLsjBNM3FtmiaNjY3861//SvTEDKZMn8rclQQsSbKHsTIpYIHMa48QQohk5OXlkZeX1+Nje/fuBQY3x8Xv9/Pmm2+yYcMGCgoKBu15UkkClj7IqCEhWflQCCGGpaGogPvoo4+yZ88eysrKuOSSSwbteVJJ5ukmLdN6WDKtPUIIIVKhYzLLYM6U7Sg1Ul9fz1tvvYVlWYP2XKkiPSxJk1lCQgghBl8oFGL06NHk5uYO2nPMmjWLKVOm8Oabb7J8+XLmzJkzJOvyDYQELEmKmUE+3H4vbx6oBzTQ9MQQkaZpgB6/ti+apiUKzdm3O7brdPSMtIf2Ylkqnj5rAQqUlbivKYX9qGVfK5XYr6r9nwAse3kiAAsWLiPPN27wfxFCCCEGVTgcZuLEiYP+PC6Xi+LiYoCsyGORgCVJm7TZVJlbyGl8BA0LDYWGwp7uTPz6UNvs23r8MT0eknSsgNSkjYhv0bscYd9G6zirHeh0PN6oj6LY2pto3572RqZLwCKEEFkvHA4PWeHUPXv2UFRUNCRr8g2UBCxJusO4hevHVfC1qhH9PodSHb0pNkvZYYiu9z+VaGVzG+e/t5XXfdP6fQ4hhBCZQSlFKBQasrooVVVVrFq1ij179jB69Oghec7+kqTbJMUUOAeYw6JpGnqXi0PXBxSsABjxNplSl0UIIbJeLBbDsqwh62GZOXMm5eXlWVFxXgKWJEWVhVPPvKTbjvWjZZazEEJkv45CbkMVsOi6zty5c6murs74InISsCTBUoqYAlcGzhLSO3pYJGIRQois1xE0DNWQUCgUYvXq1YwdOzbDFhw+mAQsSYjGg4FM7GHpaJKZ3mYIIYRIgVAoBAxdD8tLL72E3+/nU5/61JA830BIwJKEqBUPWDKwh8WQHhYhhBg2hnJIyLIs1q5dywknnEBZWdmgP99AScCShEg8GHBlYg9L/FriFSGEyH5DGbAEg0FisRglJSWD/lypINOakyA9LEIIIYZCx5DQYOawKKXYvn07r7zyCoZhMGrUqEF7rlSSgCUJnT0smdchZUgOixBCDBvhcBiHw4FhGL3v3A81NTU8/fTT7N27l5EjR/KFL3yBoqKiQXmuVJOAJQnSwyKEEGIoBIPBQRsOCoVC/N///R8+n49LL72USZMmxZeUyQ4SsCQhouxVLDMxh6WjRRKvCCFE9lu+fPmgnjsSiXDllVdmxdpBH5d5YxwZKNHDkoEBS0evT0QiFiGEyHrl5eWDcl6lFO+//z4LFizIymAFpIclKR0BSyYWjnPH82oilpXmlgghhBio0tJSvF5vys/b1NREIBCgqqoq5eceKtLDkoRIBheOc8fbFLakh0UIIbLdYC18uGrVKgzDYOzYsSk/91CRgCUJmZx02xSz5wdJ0q0QQmS/cDic0qRby7J48cUXWbFiBZ/85CeHrOT/YJAhoSRkcuG4ze32nP2WmExsFkKIvmp5+hlCGz9C0w1wGGiGA83QIXFtdD6m21ONfccvwlFaiuZ2o6V4+nGqe1ieffZZVq9ezemnn86iRYtSdt50kIAlCZ09LJnXIbW4JD/dTRBCiKxV+/OfQSSKnp+PMmNgWijTBNO0r2MxlNW5jY/nCzqd6G43mtuduNY8HnSXC83jQXO70N2e+HZ34rbucaO5Ora50dz2vm3Nzez68EM2Ak6PB6cnB2eOB5fPh9PrxeX14vT5MJxOABo2b2bnqlVY27bhnTyZnIqKxH7b6+tZvXo15557LvPmzRv6X26KScCShEzuYQHwGToRyWERQog+U4EgpddcQ8nlX0pq/9CmTUR27UKFI6hwCCscRoXCqEgYKxRGhbvftsIhrFAI1dyMFYnvGw7bx4XDqFAIKxKBWAwA51lnsj8W45GVKw/bDt2y0E2TWDxwAWDTJvvSxTFTpgyLYAUkYElKNB5RZ2IOC9iJtzKtWQgh+kYphRUMouckPwTjmToVz9SpqW9LLIYKhxnX3k6gpYVIIEA0GLQvoRDRcNi+hMLEIhGi0QixaJRYNMroSZMZUTmSmK4Ti5lEggHq/ng/sd27OOGmm1Le1nSRgCUJmd7D4tJ0wjKtWQgh+kRFImBZ6Dk56W4KmsOB5nCQ4/ORM2LEgM+n//oOPJ/4BMYQLKI4VDIvKSMDRS2FTmcZ/Ezj1jWZ1iyEEH2kgkEAtAwIWFJNhcMYvtx0NyOlJGBJQkSpjO1dAbvnR3JYhBCib6z4ysiZ0MOSau4Z0wmsfS/dzUgpCViSELVUxuavgF3tVoaEhBCib6x4D4uexbVJemI2NxPbtx/dNXyGg0AClqRElcrIKrcdXJJ0K4QQfabiPSyaZ3j0sCilaHzwQbaeupjQli2UfPmKdDcppSTpNgkRS+HKwBosHVyaDAkJIURfWcGOIaHh0cNSf+edHLj7HoouvZTSr12Fo6Qk3U1KKQlYkpDpPSwyJCSEEH2nQvEhoWGSw9L28ivknX46FT/4frqbMigyt9sgg0QsKyNXau7gkllCQgjRZx1Jt8NlllDOvKMJvv++PV17GJKAJQlRpXBkdA+LDAkJIURfWYHhlXRb+OlPE6utJfDe2nQ3ZVAMKGC5/fbb0TSNb3zjG4ltoVCIq6++mpKSEnJzc7nooouora097HmUUtx8882MHDmSnJwclixZwpYtWwbStJSKWAp3BvewyJCQEEL0XceQkDZMAhbNYWd5qEg4zS0ZHP0OWFatWsW9997L7Nmzu22//vrrefrpp3nsscdYvnw5+/bt48ILLzzsuX7+859z5513cs899/D222/j8/k444wzCMW769ItYmV2DotT04jKLCEhhOgTKxBAy8lB04fHYEPTw3/FKCnBu3BhupsyKPr1v9TW1sall17KfffdR1FRUWJ7S0sL999/P7/61a849dRTmT9/Pg888ABvvfUWKw+xkJNSijvuuIPvf//7nHfeecyePZsHH3yQffv28dRTT/Xrh0q1bCgcF5UhISGE6BMrEED3etPdjJRQlkXbq69ScM456C5XupszKPoVsFx99dWcffbZLFmypNv21atXE41Gu22fNm0aVVVVrFixosdz7dixg5qamm7HFBQUsHDhwkMeEw6H8fv93S6DyU66zdwI3K1rhKWHRQgh+sRqHz4BS2TXLmK1tfhOOCHdTRk0fZ7W/Mgjj7BmzRpWrVp10GM1NTW4XC4KCwu7bS8vL6empqbH83VsLy8vT/qY2267jVtvvbWvTe+3iJXZPSxOTZceFiGE6KPh1MOiOZ32tZG5X64Hqk8/WXV1Nddddx1/+ctf8KQxSemmm26ipaUlcamurh7U54tm+JCQvfihJN0KIURfDKeAxTliBGga0X370t2UQdOngGX16tXU1dUxb948HA4HDoeD5cuXc+edd+JwOCgvLycSidDc3NztuNraWioqKno8Z8f2j88kOtwxbreb/Pz8bpfBFLZURtdhcesaIelhEUKIPrGCwWETsFiRKGgaZmtbupsyaPoUsCxevJh169axdu3axOWYY47h0ksvTdx2Op0sW7YsccymTZvYvXs3ixYt6vGc48ePp6Kiotsxfr+ft99++5DHDLVohs8SKnA6aInFUJLHIoQQSbMC7WjDoCx/25tvsuPcc9GcTnyLjkt3cwZNn3JY8vLymDVrVrdtPp+PkpKSxPYrrriCG264geLiYvLz87n22mtZtGgRxx3X+UucNm0at912GxdccEGijstPfvITJk+ezPjx4/nBD35AZWUl559//sB/whSIqsxeS8ihgalAy+BeICGEyDQqEMQoKEx3Mwak7bXXqL7yq3gXLqTqTw/gqqpKd5MGTcrXEvr1r3+NrutcdNFFhMNhzjjjDH7/+99322fTpk20tLQk7n/729+mvb2dK6+8kubmZk488USee+65tObJdGUqhZHBsUDUUjglWBFCiD6xQqGsX0co9NFGNI+Hqv+9H80w0t2cQTXggOXVV1/tdt/j8XDXXXdx1113HfKYjw9daJrGj370I370ox8NtDmDIpbhix+aCgwJWIQQok+sYDDrA5acOXNQoRDhTZvwzJiR7uYMKlmtOQltdQGe39jExvc+tsRAbykjBz1ub1AKdgXD+GMW03M9WEphKXu7hcICLEthWgrLUvbjliIUNCmryqN8UiGmsnt+TKWoDkVwZu6IlRBCZCQrGMi6HJbmxx/H/+/n0H0+fIuOI/+ss9Dz8mh55lkJWATENjXT1BiiwaXbMcehOjMO18vxsYfM+PX6umC3QzVAQwMddE1D00DTNXRNo60hSKA9QtnEQhyavYaQoWmUupzMys3ubwlCCDHUVDCEnpM9s4Qie/aw//s/IGf+fFQ0Ss2Pf0Ldr+/ACgaJbNuW7uYNOglYklCiGVxw3DhuPie90eutT2/gjS0N/N/sCWlthxBCDAf2kFD29LCooP0Ft+jiiyk451NE9+6l+Ym/E927h5Irr0xz6wafBCxJaA/HyHWnP5nJ5dCJmFIgTgghBkpZFioUQsuiHBb35MnkLllMzQ9/iGtsFTmzZ1P29WvT3awhI5kPSYiaCkcGlDt2GzqRmAQsQgiRjJiliFqqxxpVKhQCyKohIYBRP/857smT2ftf/4U6wiqcSw9LEiylMDJglpDLIQGLEEIkoz1mcvSKDfhjFhp2RXCXruHSdNy6hkMp+MEvcLVYuB76By7LwqUsnErhQuFEw62BC+zjdA23puMyNNyGwVP5pSwwQ8zFIsdpkON04nE68bqdeNxu8n1eJowdg66n9suu7vWSf/ZZ1P70NqL79uEaPTql589kErAkIWZaGRGwOA0ZEhJCiGQciMbwxyy+NmYE470uwpYiYikilhW/beFvrCUUChFBJ6IgoiCKIoBGBI2IphHRdKKaTkTXiRoGEd0gajhod3rY6vTwcMcTWkA4fiEM9WHY2URRmx93LIbHjOG2TDyWRY5l4dYUOQo8GuToGh5dI8fQydF0PIZuB0GGgxynA6/TgcdhUL5hPcb992E2NuKZPRtnZWW6fr1pIQFLEqwMqXPiNHRippTfF0KI3gTj66stLc1nQWFuzztNGjWg57BMk1AoRCAQJBgKEwyHCYYiBMJhVu3aS0wpQqZJMGYRtCxCShFUEEYjqGnUazohXSekDMI4COtOQg4nYaeLiMvV+URR+zLBU8Kj8+fjPfYYij7/ebQU995kOglYkmBamTEk5HToRKWHRQghehWMv1fmDGL+oW4YeH0+vD7fQY8tmj+n3+dVSmGGw3YwFAzRFgpz/M4mTjr6KEZfes5AmpzVJGBJQqYELC5DIxYvJqdnQHuEECJThazBD1gGi6ZpODwecj0ecgthBKDvbGJbOJbupqVV9v1PpoGZIUm3zvgfXvQIywwXQoi+SvSwDJNhkzPLCsiAj6G0Gh7/k4MsU3pYEgGL5LEIIcRhBeNf7DzDIGBRSrGlPcxoj6v3nYex7P+fHGRWPHErU5JuAaIytVkIIQ5rKHJYhsKm9hAXvLeVzYEQnyzOT3dz0kpyWHoR6whYMqCHxeWw2yCJt0IIcXgds4Q8GfDe3R/1kSi/3FHDQ/sPMM7j5rE5EzmpOC/dzUorCVh6YanMCVg6c1hkSEgIIQ4nZFnkxBeOzTa7gmGWvrsZBXx3QiVfHl2KexgMbQ2UBCy9MOPBQSbMypEhISGESE7QtLI2f+XBfQdoipmsO2EmZS5nupuTMbLzf3MIdfSwZEC8kijL3xyMprklQgiR2QKmlbX5K4vjuSq/3lmL2cM6SEeq7PzfTAON9Ecs1U0BALbUtqa5JUIIkdmClpW1U5qPL8rlZ1NG8797Gxj16vu83xpId5MyQnb+bw6hTIptZ4y0o+5xpQdXVRRCCNEpZKms7WEBuGxUKQ/MGgfA5z/YTnvMTG+DMkD2/m8OkY7euEzI28p12ylHmTA8JYQQmSxoZm8PS4czywp54ZgpBEyLr2/cne7mpJ0k3famI2BJbysAcEjhOCGESErIsviwPcjp725Cj7+DnzeikKuqRqS5ZX1T6nRwYlEuK5vb092UtJOApRcqHrFkQg+LI961Iis2CyHE4X2hsoQCh4HC7il/aP8BvIaeNQHL+60BvrWxmnVtQQCuzpJ2DyYJWHrRmaCd/ohF1hISQojknFiUx4lFnYXWmmIxAllSdLMlGuPC97YyIcfNfTPHcVyhT6Y3IwFLrzrilYzoYTGkh0UIIfojbCncWZIAuC8cpd20+PHkURxXmJvu5mSM7M5IGgIq3sWSCS9zZzyBLJYl3xKEECJTRCwLV5Yk4XZ8JXVlwjflDJId/3tp1FEFPxPKO3f0sEhpfiHEcKeUwjStxJfGgYpYKmsCgPb4l1JnlvQIDRUZEupFRiXdJoaEpIdFCDG8/evudez8oAGAKQvLOe3ymQM6XzYNCb3S6CfX0Jnmy0l3UzKKBCy9yaA6LB1DQrJasxBiuPM3BBk9rYhIMEb1h40se/AjdF1D1zVGTS1i0vy+zZqJqOwYEopZir/XNnFmWYH0sHyMBCy9sBIBS/pfOLquoWtSh0UIMfwpBSWVuZRV5bLhjX0017RjmYrWpjC7P2qkrCqX3EIPhjO5ICRiKVwZFgDsCoZZ1dJOS8zEpWsUOhw819DCzmCE+2aOS3fzMo4ELL1IDAmluR0dHIaeWEFaCCGGLaVAg6nHjWTqcSMTm9e+tJs3H9/KQz9YyZgZxZz79blJnc7hjxLwt/JauI7jppTgchqD1PDeHYjEuHnrXp6obQLArWtELYUFVLic/HBiJUfledPWvkwlAUsvVAb1sIBdPC4mAYsQYphTih6/Kc7+5GgqJxfy0gMfUv1hIw/f+ja6rqHpUDG+gIXnTkA3NHSHhm7o6PFelaUvNJHbarKOfWw8s5Irz5s2tD8QYCnFIzWN/GTbPpSCX04dw3kjCslzGEQtRXMsRqnTkTGfN5lGApZeWBk0rRlARSO8/c+/k/P8fiC+irSmJXJsNE1H0zQ0XQNNx3A4OOmSyygbOz6NrRZCDCc1O1qo3eGnrSnMvs1NaLqG4dAxnLp97dBxOOP3nV3uxx8znF0e77jv0DGcGobDwHDqtB4I9fjBrRs6I8bms+TyGWx5tw5lKixLse7VPTRUt7H+tb3dD9DAMHRyYxbjPlnJ1uX7cKThS9+HbUG+s2kPq/ztXFRexA8nVjLC3VkMzqlrUhyuFxKw9EJl0LRmAMwoSjcorhwdTwhWndP+lH27476yLLa88xZjjzpaAhYhRErU7fLzxM9Wo+kavgIXIycV4nTpxGIWZlRhxiwiwSgBv4UZU5hRCzNmEYuanffj23rjdB06P2XE2HxGjM1P3F9wznj2b2vBMi0sU2HFLExT2bdNC2XB+Pll7HxlH/Ubmvjp269h5jnQHDqaQ0Nz6HavjENHd+gYDjt4cjh1HE4NZ/y206njchm4nAZup46hFFZLlOKqPHxeJwU+JxWFnbN7Ypbizt21/GpnDeNz3DwxdyIndKnAK5InAUsvLMte0vtrD7zBeKe9+FRn6HJwEKN9/EaXGgLdejg/tl0BltLsa0ApDQs76bfjWikIa3kUjhrD0qsuSqr993z1C0RDwaT2FUKI3rTU2+8nl//sBHLyXP0+j1IKK6bigY4dwJhRi1jH7ZhF2ZjkP9g9PifjZ5cedh/TtGiqdONsjOCMKoKGhvJpqLCJMpXdW2MqNFNhxhS6pYiZYJiKaB8mZ8742gw+ObuC9/wBbtm6l1Ut7Vw3tpzrx5VnxUylTCUBSy/yVYipbZsJO7yEfXaJ5O6hxsH3E/eUBlr3sEYlNmjdAh/dfgRNU+iAris0FLpmzwyyLxqj9DYuPPHopNvv9HiISMAiRMZ5addLvLH3DXIcOXidXrwO70HXXR/Lc+VR5ClKd7PZt6UZX6Ebt29gwxeaptlDQE4dhqjciGHofP/mE/p1rGlZhCIWgUiMUNQkGLEIRWK0t0Vp3tuOUexm1x4/kef2URuKcuWGnfyzrpkpXg+Pz53E8UVSYn+gJGDphaEpTq9fxkXf/RHj5sxLd3P6zOnJYeNbrxGLRNj67krKx0/kvG99P93NEuKI96cNf2K3fzfFnmICsYB9iQaIWtFDHvOH0/7AospFQ9jKg21fW8+UBRWJZNYjhaHr+Dw6Pk8PH5vxmnavGhob2MePaupwlLj59bQxfLaiGCNTUgqyXJ8Clrvvvpu7776bnTt3AjBz5kxuvvlmzjzzTAC2bdvGt771Ld544w3C4TBLly7lt7/9LeXl5Yc85y233MKtt97abdvUqVPZuHFjH3+UwWHF7CEh3cjO2K6wvIItO7ez8/3VtDbUEwkG0t0kIQRQH6jn01M+zdfnfb3b9qgZJRALEIwF7etokK3NW/n+m9/HUukvGhkJmdTvbqW+upXS0bkyoyUuEoqx/+06FODLc/H4vMmMzXGnu1nDSp8+hUePHs3tt9/O5MmTUUrx5z//mfPOO4/33nuPcePGcfrppzNnzhxefvllAH7wgx9wzjnnsHLlSvTDjNvNnDmTl156qbNRjswJDkwzBtiZ6dnoU9d9h0goiMeXyzN3/Ixga0u6myTEEU8pRV2wjjJv2UGPOQ0nBUYBBe6CxLaOXpee9h9qhSNy2LupiUf/exWfuemYbomvR6r63a28+MCHtDaGmHDReFaeMk56VQZBnyKDc845p9v9//7v/+buu+9m5cqV7N27l507d/Lee++Rn2+/gP/85z9TVFTEyy+/zJIlSw7dCIeDioqKfjR/8Ckzu3tYdMPAE8+9aW9uIre4JM0tEkI0h5uJWTFG5CRXXr4+WA+Q9P6D6cJvzWf3hwd47t716MaR/aGslOLDN/bx2t82UzzSx6e/M5+SSslVGSz97jYwTZNHHnmE9vZ2Fi1aRDgcRtM03O7OLjCPx4Ou67zxxhuHPdeWLVuorKxkwoQJXHrppezevfuw+4fDYfx+f7fLYDETAUv6qiKmSntzE77C9CftCXGkqwvUAcn3mNQF6nDqzm69LunidBs44lViPb7+zxLKdtGIycsPfsSrf9nEjOMr+fS3j5FgZZD1udtg3bp1LFq0iFAoRG5uLk8++SQzZsygrKwMn8/Hd77zHX7605+ilOLGG2/ENE32799/yPMtXLiQP/3pT0ydOpX9+/dz6623ctJJJ7F+/Xry8nqe0nbbbbcdlPcyWNRwC1iKitPdDCGOeIkeE2+SPSyBekZ4RwxavkjN9hbeeXo7utFZ0E1ZimmLRuL0OCgfl9dtWDzUFgHAk5udPc8D1d4c5pm73qe5JsDiL01nWpelA8Tg6fOrberUqaxdu5aWlhYef/xxLrvsMpYvX86MGTN47LHHuOqqq7jzzjvRdZ1LLrmEefPmHTZ/pSNhF2D27NksXLiQsWPH8uijj3LFFVf0eMxNN93EDTfckLjv9/sZM2ZMX3+UpHT0sBgZlFfTH9FwiEgwID0sQmSA+oAdsJTkJDdEWx+spyxn8PJXdq0/wP5tLYyZXkw0bLLrw0ZiYZMt79o9QS6Pwfi5ZfEiagYH9rXh6NLTciSJRkz+eedawoEYF31nPqWjpQjcUOnzp7DL5WLSpEkAzJ8/n1WrVvGb3/yGe++9l9NPP51t27bR0NCAw+GgsLCQiooKJkyYkPT5CwsLmTJlClu3bj3kPm63u9vQ02Dq6GHR9Oz+w2xvbgbAVyABixCptq5+Hb957ze4dFeidkqOI8e+Ha+nkuPsvL2mbg3FnmKcenK1TOoCPSfopkqoLUrBCC9nXTW7c1t7lGjYZOVT2wj4I/jrg8Q6CrtFTcbOPDJ7a1/63w/x1wf5zE3HUlzpS3dzjigD7jawLItwONxtW2mpXW3w5Zdfpq6ujnPPPTfp87W1tbFt2za+8IUvDLRpKdExS8hwZHvAYq8K6issTG9DhBiGlu9Zzgf1H3DcyOPwR/zUBGoIxoIEo8HEFOVgrHsBx6NHJF8Asj5QT0u4hXvfvzcR/HgMTyIA8jg8iQCp477X4cVpJBcQhdqjeD5WCM7jc+LxOTnt/81Mup3D3fK/bmL72no++YVpEqykQZ8ClptuuokzzzyTqqoqWltbefjhh3n11Vd5/vnnAXjggQeYPn06ZWVlrFixguuuu47rr7+eqVOnJs6xePFiLrjgAq655hoAvvWtb3HOOecwduxY9u3bxw9/+EMMw+CSSy5J4Y/Zf8Olh8WM2mPO+7dtprRqXHobI8QwU9New+TCydx56p2H3MdSFqFYKBG89KVq7dwRc1m5fyUPb3yYYCxIKBZC0fsCfg7N0WMw03G7ZM8EZoTnU7c6ysR56Z+BlKks02Ldq3tZv3wvo6YUMuOEynQ36YjUp4Clrq6OL37xi+zfv5+CggJmz57N888/z2mnnQbApk2buOmmm2hsbGTcuHF873vf4/rrr+92jo4how579uzhkksu4cCBA5SVlXHiiSeycuVKysrSX28Ahk8OS9HIUYAMCQkxGGoCNZT7Dl0gE0DXdLvMvtPb5/Pfcvwt3e4rpQib4UTw0xEIBWKBbkFR19tB0+7xCcaChEx7O2uLqTEDFI3Ip2rGkTnE05OGPW1sWrmf5toALQ0hWhvs4bCjPjmakz47Od3NO2L16VP4/vvvP+zjt99+O7fffvth9+moktvhkUce6UsThpyVKByX3T0s/no7eS6/NDMCQSGGk9r2WqYUTRmy59M0DY/Dg8fhoYj+fwn5xT+fRJ/VzOe/ckYKW5e9lFKsenYnq57ZgTffRdnYPEZPK6KgtJLKyYWUVUmCbTpld7fBEDBj8RwW58AW+ko3f0M8YCmTbl8hUkkpRU17DRXezCx+eShKKZwxDx7vkV38rYNSipVPbWfN87tYeO54jj5jLEaWVjgfriRg6YUZtUtiZ/uQkL++Dk9uHq6cvndHCyEOrSXcQsgMUeHLroClLdSO03Tjy9BOA6UUuz9s5P1l1QT8EXJynVTNLGHmSZW4elqAcIDP9dYTW1n7UjUnfHoSc5dUpfT8IjWy+1N4CHT0sGRraf4O/vo68kuld0WIVKsJ1ABkXcDSEJ85mJeXebNd2pvDvHD/BvZtaWbEuHxGTiigrTnMyie3seb5XZx88RQmH3P4nKG+2L62nrUvVXPS56Yw+5OjU3ZekVrZ/Sk8BKxYDMPhyPoVSf0H6snPkERmIYaTmvbsDFgOtDQDUJiXWeXk63b5+dfvPwBN41PXzqFqRnHi/dd/IMhbT2zjhT9uAAWTj00+aLFMi01v11KzvYXm2gD11a04nDrFlbm0N4fJLXJLsJLhJGDphRmLojuyO38FoO1AA6NnHJXuZggx7NS01+DQHJR4smth0aYWe+X2osLMWG3ZNC0+emMfbzy+ldLRuZz5n0fhK+heIDS/JIczvjKTZ+8yWfPCrqQClpb6IFtW1bJxxX5a6oOUjsmloMzL/KVjMWOKhupWjFIP85eOHawfTaSIBCy9MGOxrE+4BWhtbJCVmoUYBDXtNYzwjsDIslpNfn874KS0ML3TmSPBGFvX1LH63zvxHwgx4/iRnHTxlEOW/dc0jRknVvLve9ZxYG8bJaN67iFq3NfO2//czva19TjcBuNnl3LGV2bJTJ8sJgFLL8xYFCPLpzRHwyHC7e3klZSmuylCDDs1gZqsGw4CaGsNAk6K89OzArRlWqx5fjer/72TWNRi/JxSzrpq9iEDkK7GzirBk+tkw+v7OPni7tPJm2sDvPP0drasriOv2MOpX5zGpPnlON3Z/T4uJGDplWWaWZ9w29Z4AIDcIulhESLVatp7LxqXidpbw0SMEA7X0H+QxyImL9y/gZ3rDjD9+JEcc9Y48oo9SR9vOHTmLhnDyn9sJxKK4St0oyzFgb3t7NnYiDffxScunsL04ysxnDI1ebjI7k/iIWAHLNn9gk8ELDIkJETK1bTXMLtsdu87ZphwW4yoO5SW517+yGaqP2rkrKuOYtxR/ev5nXe6nXOyZVUt+7Y0o+ka+SUejr9wEjNPqkxLICYGlwQsvfjgpecItbWmuxkD0hoPWPIkYBEipSxlURuozbqicQDRdosIIdZ8tIFp4yfi9STfwzFQezc1MevkUf0OVgA0XWP+0nHMXzoudQ0TGU0Cll4oZaXsXPXrtlH7/IeocAzd58RR4MFRnIPmNNCdGjh0nD4PvtIScitKcXhdAFiWCUrrd09PW+MB3D4fziF8QxLiSNAYaiRmxbIyhwVLoyhQwYrf1PLypLV861uXDsnTKksR9EfwFbp731mILiRg6cUJsz5DSW0Zu7+z/KDHFAqlLBSKziotXW51q92iYWgGOZabsG7haNFx7zcwNAuwupwzRBvNtLEtsS1qRTA0g5AWIOwMo5SFoTvQnDpajo6e40T3OiDHQM9x4M7z4iktJLeyBHdxHm2NByR/RYhBkK01WACu+vr5fLRtO2/dvY+crSO5/Za/MP/08Zx2/PGD+rwt9fZCgsWVmVewTmQ2CVh6UVkxhZC/ieDYyMEPKs0OT1T8nx5qyylIbNcMk7GfOg5PsV33IBaJEmpoxgybqIh9ibQFCDQ3E25oxbVNxxVyEZ2qaIu0YjaEcIQd6LoD04pBm8LwG+gKnLqBQ9exg582QrQRYg+WshhljmaUezS1v1mTaKvmcaDnxC9eJ5rbwFGag3dOGZqe3UXyhBgqzeFmAC599lJynDn4nD6q8qr4w2l/yPhpznneXBYcNZvtZ+5l94Z95Owu5cP3dg16wFJfbQ+xl42R6cWibyRg6YXT5UErK2Ds5XNTfm6Hy0luZWqqz1qmSTQQItoaJNjoJ9jQTKjBT+RAO6Y/TGFhBa6y/ETwpEImVjBG7EAIq7qVWH0QACPPiWdS/1d/FeJIsqBiAb84+Re0hFtoj7WzqmYVb+17C2V/M8gKF59zJpwDv7rmaby+/tWcCvgjNO5vJ9QWRTc0nC6D3GI3Lo+D1sYQOXku8ks9aJpGS30Qj89JTp4rxT+JGO4kYOmNpSALehx0w8Cd58Od5yO3su+JbJH9bdT95j0O/OUjPBML0dwOdI9h98S4DTSPgZ643eXaY6C5DOmVEUckl+Fi6filifuhWIhNjZtw6Nn31uow3QRXGfxi7ZMo3ULpJspQoFtgKDAUmgM0h+ITZx/FwtlzCLVHee2vm9iyuo7eYrTiSh+jphZRt9NPTl72F+MUQy/7/qqGmqLHoZ7hJPhhA02PbwFA9ziwIhbKH8AKmahwLH5tHvYcmsuIBzgGutuRCHA0t9EtuOn6mKlrBA0NV74Ll9uB02NgOLJ7Crk4stUF6hjhzc5FRivPhfr9bZgxhRm1sEyFFVNYMVAxUKZ98e6t4L01Wzhm5lE887v3aa4N8IlLpjJ6ahE5eU4sUxENm/gPhIgEYuSVemhrDLHl3TqqP2wkHIhywqcnp/vHFVlIApZkDNOApe3dGlqe3m4HIxrknlhJ/lnj0fWDgwZlKVTExAqbqFBnEGOFYonrnraplrC9PRSzj/1Y4LM/YvFOoHObbmg4PUYigHG67YvL47BvewzGzixh3Gyp2isyT12gjjJvdi4y+ukzT+91n3A0zB+ufZ3c3Bzqd7dSu8PPOV+fQ9WM7kn9OXmQX5qTuF82Jo/xc7Lz9yIyhwQsR6j2NbU0/30rAL6FIyk4cxy659AvB03X4r0kDijo/3TEROATMtn+81W4C92c++UpRMIxomGTaMgkGjaJhDrvR+Lbgm32OPmBPW0SsIiMVBeoY+6IueluxqCpaapHR6ewIBeXO/5+kT3pOiLLScByhLFMi/rfryW6tx2A/LPGk3/y0C2p3hH4aG4Dh2nhHOFlzIzkF1974f4NBPzhQWyhEP2XzUNCyag90ABAcVEBBWU5OJw6296rp2qmlE0Qg08CliNMdLc/EayM/O4C2tfU0bZqP7nHjhzSdgQagrg0DSq8fTrOMi2MLF8qQQxPETNCU7iJspzhO/RR39QEwAd/buID9RpmzKJ8XH6aWyWOFBKwHGHc4wtxjcsnstPP/p++k9hutUTIXzJ2yNrh39YCgK+PS72bMYUuibkiA1iWxbJly4hEIjidTkKEmNwymXXvraN5ZzNetxevx4vP4yM3J5e8nDzyvfkUeAvwurw95oplMqUUz9Y/RWnxLE6ecjxlY/IZM71YCsCJISMByxGo9PJZND+9DSyFY4QX/3M7aV9TN6QBS3t1Kx6gYGJhn46zTAunLGomMsCBAwd48803KS62hzRDkRAzAjOINcbYxa7DHqtQxPQYMS1GTI/hcDrAAM3Q0JwahsNAd+jotTqG1yBndA5OpxOX04XH5cHtcuN2uclx59iBkcsOjnI9ufjcPnweHx6HB11LXVC0vmE9rze/zG1fPo0lE2am7LxCJEsCliOQ7jYo/vQUrKjF/v9eCUD+aUMXrABEagNoCjx9TOA1Ywq3N7u+mYrhye/3A/D5z38+EbSA3fMSioZoCbTgD/hpDbbSFmyjLdRGIBQgEAoQjoQJhUOsqF5BubucfGc+ZtTEillYUQszaGKaJu6IGzNi0uxvRrd0dJJ/7ZuaiamZWLqF0hVKV3ZQpGt2YOTQMAwDw2FfHE4HTocTp8uJy+FKBEW6Q+fNljd5o+kNxheMZ3HV4pT/LoVIhgQsRyjLtNj/05WokIlvYQW+o4c2UdBqDhNx9j3wsHNYhuk8c5FVWlvtEvN5ed2HNXVdt3s93F5GFh0+N+w6ruvTc5qmSSgcoj3cbl9C7QTCAQLhAMFwkFA4RCgaIhwJE46EiUQjRKIRYtEYsZh9MWPxwMi0MMMmMSsGJmiWlrgYltEtOCowCvj+Z7/P0vFLyXHkHKaFQgweCViOUJY/ggqaYGgUXTD0RZyMQBQrv++luSWHRWQKv99PTo49VDNUDMPA5/Xh8w5+3kg0FqUt1MbmrZv591P/Zo42hzyXrP8j0kfe+XujDl1kQMUsorXtmK09LIyY4drfsVeZLVg6bsifWymF27Qwijx9PlZ6WESm8Pv95OcP3xkyToeTotwiFsxZwKhRo1i5cmW6mySOcNLD0gulQNMO/oBsX11Ly7PbsQIxABzlXvJOGoV3XnlWrKsTa7AXO/QdN7TTmQHa6+wpzdrIvn9LlB4WkSlaW1sPGg4ajjRNY9q0aSxbtoz6+nrKyobvtG2R2SRg6YfW5dW0/Hsn3qNH4Du2AtMfJrjeXo8nvK2Fos9MyfigJdYQBENDdw79jJuWbc0A5PZxSjOAFbMwHJn9uxVHBr/fz8iRQx/wp0PHz9nc3CwBi0gbCVh6ozpXa1ZK0bp8D/7ndpJ36hgKTh+X2M07dwSB9+tofGQTwKAELUopgusbCLxXjwrHcI7KJff4UTgK+14q3/SHD1uKfzAF9rSSA+T3cUozgGla6FI4TmQAv9/P1KlT092MIdExC8owpKSASB8JWHqjILy1mQMPf0R4px/LHyFvcRX5S6oO2tU7ZwSg0fjIRjSnTuEFk3ocTupXMyxF0xNbCKyuxTU2HyPPSWB1Le2raim7cjauPg6vWEETZz+GZFIhUhtAB9x5fU+6tWJKelhE2pmmSXt7+xExJASQk2PPDAoGg2luiTiSScDSCz3H/hXFGoJ4jx6BZ0oRnsP0DHjnlKFiFk2PbSZ2IIhrXAFGvouc6SUYScyKCbxfT3BDA0auC+/RI3BWeIk2hGhdtovghwco+uwUfPPKAbACUer/uI4DD26g4lvHoCXZ82AFYmApnOV9K4ufKqqlf1OaQXpYRGbomNI8nJNuu6qtrQWgsLAwvQ0RRzQJWHpReM5E8pdUYeQnP+zim1+O7jZofXMf7e/sx2qL0vKvHeQvGUvu8ZVoPcxysSImzU9tJbCmDteYPCI7/bS9tS/xuO51UHzxNLyzy7psc5J/ahUHHvoIsy2KI8kibKHtzQC4xqTn26ERiKH6ueKz3cMiAYtIr46iccMtYAkGg4RCIQoKChJLB+zatYt//vOfFBQUHDE5OyIzScDSC82pYzj7/uGaM6uUnFmlgN0T0vLiLlr+tZ3Ae7XkHleJUeJBxSwiu1uJVLcS2d0KpkXRZ6bgm1+OshThrc2Y7VGMfBfuqny0HnoldK9dA0IFY5BkEBDZaa/j455U2Oefa6A6pjRHi/s+pRnAjFnoMq1ZpNmhisZls40bN/K3v/0NpRT5+fmMGjWK5uZm9u/fT0VFBZ/73Oeybv0jMbxIwDIEdK+TovMm4ZtXTsu/d9D09y1dHnPgGpNH3omV5Mwpw1lmD9NouoZnSlGv5zbiCbdmSxhnRXI5KdF99mrNHc81lNpqArg0Db2PqzSDHexYpvSwiPTz+/04HI5EbsdwUFtbi1KKSy65hO3bt1NfX09paSknn3wyU6dOlWBFpJ0ELEPINSaPsitnY4ViWG1R0MAo9gwoMbcjYGl4YAOjfnICWhIf5rHGEJo7Pdn+nVOa+96Vbpl2ET89i5NuW4JRqhsD7GkKsKfJTmDMcRnkOA08TgOPU8fjMPC4DGaMzMeThmnnoncdReNSlVSfCTryU/Ly8jjzzDPT2xgheiABSxroHkfKphRruoZR6MZsDrP3+2/iPXoEmsfA8DnRfU6MfDeuMXndEn7NtiiOov7lkAxUcE8bOfR9lWaAaNgEwJHBH+KhqMmbWxvYWNOKz2VQ3RRkT1OA6sYg1U0BWkOxxL4ep46haQSjJlYPBZUXjCvm4a8sxCFJxhlnOBaNmzVrFm+99RZPPvkkl156qSTYiozTp0/Nu+++m7vvvpudO3cCMHPmTG6++eZENL5t2za+9a1v8cYbbxAOh1m6dCm//e1vKS8vP+x577rrLn7xi19QU1PDnDlz+O1vf8uCBQv69xMdgUbeuIDI3jba39lPtCaACscw22NYgSjEeyWMYg/euWX4FlVCzMJRmp6u7EhdAA1w5vZ9/ZVQWxSAnLyhW7ulJ5GYxc4D7Wyvb2fXgXZ2HmhnZ0OAnQfa2d8SSuznMnRGFeUwuiiHOWMK+dSckYwp8jK6KIcxxV5KfC40TUMpRdRUBCMmoZhJOGrxzcfW8s7ORpb8ajn/89k5zB9bfJgWiYHa+cF7bHv3bdxeH26vF7fXhyt+7U5c2xeH243f76egoCBt7TVNk0gkgtvtTtlQjWEYXHTRRTz00EPcddddLF68mAULFshQkMgYfQpYRo8eze23387kyZNRSvHnP/+Z8847j/fee49x48Zx+umnM2fOHF5++WUAfvCDH3DOOeewcuXKQ77o//a3v3HDDTdwzz33sHDhQu644w7OOOMMNm3axIgRQ7uCcDZzjcrF9bFFDJVSWP4I4d2thLc10/bGXlpfrgY6k3WHmmoOE3H1r4ckGF+zqXanHzNqoRkauqbZ17pmd8939NB36bFQHXd66MWImRb7whFyCj04HRpOQ8dl6DgNHV2HvU1BttW3s7Wuja11bWyvb2NXYwAz3iXicxmMK/UxrsTHvLGFjC3x4TJ0JpT5mFVZgJ5E8UBN03A5NFwOnQLs/5dHv7qIFdsP8N/PfsRFd6/g64snc8WJ4ynISW+wNlytfuZJ9m3eiNvnIxIIEA4GDrmOmKbrtE2chW/KlCFto1KKN998k7fffjuR9FtYWMjSpUuZNm1aSp5jxIgRfO1rX+Pll1/mueeeY926dXzuc58bdrOhRHbSlDrM6n5JKC4u5he/+AVjxozhzDPPpKmpKfHibmlpoaioiBdeeIElS5b0ePzChQs59thj+d3vfgeAZVmMGTOGa6+9lhtvvDGpNnR822lpaZE/rMMw2yI0PbaZ0KYmjGIPFdfPQxvi4ZWNN72BWexh5n8d0+dja3f6efz2d1PepnZN8fuC0GH3GVWYw8QRuUws8zFpRC6TynIZX+ajLNc9qHkMUdPiO098wBtrP+J/cu7n+GlVGCOPgsqjYfQCcKWnls5w8+C3r6Vy6gyWXHEVAMqyiIRChANthAMBwoF2O5AJtBMOBHjq9RX4DI1R5eU4XU5cbjdutwe3J37t9eLJySHH6yPH6yXHl4s3Lxenq/+vl48++oi//e1vzJs3jzFjxuBwOPjggw/YsmULl1xyScqr7u7evZtHH32UkSNHcumll6b03EJ06Mvnd78TKUzT5LHHHqO9vZ1Fixaxbds2NE3D7e7MjfB4POi6zhtvvNFjwBKJRFi9ejU33XRTYpuu6yxZsoQVK1Yc8rnD4TDhcDhxv6Mmgjg8I9dF6eWzCG5p5MCfP6L52R0UnT9pyJ7fill4LItwSf+mNJePy+eK/zkJM2phWQpl2bOGOmYPHRx72x8MPX4+xLf935/Xo/a088y1JxIxLWKmImpaidsjCzyML/Xhc6cn3ctp6Pzqs3N5u2w3C5evQn24BjY8YT9YPgu+8go4+l4xWHRXv2sHofY2iAcsmq7Hh4J6DgiXrXyHQDTGlv01KDRIdthEKTRloSmFDvZF1zA0DcPQcegGhsPA7XJx/n98ntLyisShK1eupKqqinPPPTexbebMmTz88MO88MILTJkyJaXBc1VVFccffzwvvPACkUgEl0teZyK9+vwuvG7dOhYtWkQoFCI3N5cnn3ySGTNmUFZWhs/n4zvf+Q4//elPUUpx4403Ypom+/fv7/FcDQ0NmKZ5UI5LeXk5GzduPGQbbrvtNm699da+Nl3E5UwupuDMcbQ8vZ28E0cNWT5L6942HJqGVtn/JQE8vtQOiYQiJpZbZ9ao9OUjJCPXZ//Oqj/7PFUTpsPfLoXtr8IvJsEpN8Kir6W3gVksFrGHGqtmzUn6mG/efEu3+6ZpEg4GCbS3EWxvI9geIBQMEAoECAeD9pesUIhIJEwkHCESjRCNRolGY8TMGLGYaZ8jGiUaDhMJRlj/7juccva5BAIB3nrrLXbt2sVnP/vZbs+r6zoLFizg4Ycf5r777iMSiRAKhSgtLWXBggXMmDGj37+X2tpaXn31VSorKyVYERmhzwHL1KlTWbt2LS0tLTz++ONcdtllLF++nBkzZvDYY49x1VVXceedd6LrOpdccgnz5s1LedLWTTfdxA033JC47/f7GTNmTEqfY7jzzS+n5ZnthHe0DF3AEq+wmzcuc4IDsz2GlpO5s446aA6751LFwuDOhS88BRufhbfuhOdvgpkXQL5UIe2P1gP1AMw46ZP9PodhGHhzc/Hm5g64PR+9t5q//eNpTM3gmWee4f3330cpxSc+8QmmT59+0P6TJk3iuOOOw+/3k5eXh8fjYdeuXTz66KOce+65zJs3r1/tWLNmDW63my9+8YsD/ZGESIk+Bywul4tJk+xhhPnz57Nq1Sp+85vfcO+993L66aezbds2GhoacDgcFBYWUlFRwYQJE3o8V2lpKYZhJNap6FBbW0tFRUWPxwC43e5uQ0+i73SPA0dZDpF9bQzVEoiBPe14lCJ/QubkGWlhE2dhFhT/6hqwgD3ONf1TUPMBVL8Nmszk6C9/gx2w5JWW9bLn0GhqaADg9XdWkZeXx6JFi1i4cCE+X89/qbqus3Tp0m7blFI888wzPPPMMxQWFh7yPfhQlFLs2rWLUaNG4fH0bwhXiFQb8MC8ZVnd8knADkQAXn75Zerq6rqNuXblcrmYP38+y5Yt4/zzz0+cb9myZVxzzTUDbZrohXtcAcEPGihYOg59CHI0YvUBQpqGw5U55X9cUUVOEotSppth2ENhlhnr/kA0vnruHz4Bcy4Bwwm6w74YTtCdoBtdbjvAcHTe1h3247oBmgHBJmjeBVXHg9MDhss+1umz93HmgMNziMSg7ORvqAMgryQzApbamhoApk2dymc++1kMo+89gJqmcdZZZ9HU1MSTTz7J1Vdf3afAo62tjZqaGo4//vg+P7cQg6VPnxw33XQTZ555JlVVVbS2tvLwww/z6quv8vzzzwPwwAMPMH36dMrKylixYgXXXXcd119/fbfs9cWLF3PBBRckApIbbriByy67jGOOOYYFCxZwxx130N7ezuWXX57CH1P0JO/UMbSvqaX5qW0UfWYKWhJTcAfEHyHqyZzhl2A4So6lkV+U+d8gOxbMVB8PWI69Ara+BNEArH8cLBPMKFjRLrdj9v1Ucnrt4KXj2uE5eJszB1w++77Lawc93a694MoFTwGUTk5bEOSvr8dXVIzDmf4p47FIhPrNH4KRw6fOOadfwUoHwzA477zz+N3vfsdzzz2X+FLYk8bGRg4cOMCIESMoKCjA4/Hg9Xp5++23mThx4iF7d4QYSn0KWOrq6vjiF7/I/v37KSgoYPbs2Tz//POcdtppAGzatImbbrqJxsZGxo0bx/e+9z2uv/76bufoGDLq8LnPfY76+npuvvlmampqmDt3Ls8991yvxebEwDkKPRR/egqNf9uEipgUfXbKoPa0OMMxwmlYv+hQqve1AVDUz1lLQ8nQ7f8XyzK7P1A0Dr526Bl1CUrZAUxH8GJGO++rju0mhJqhudo+r2WCGbEv7fV2b0ssbAdH0WAP111ut9V23o6027c7rntyyd9g6tKeHxtkrQ315GfIcNCqp58guGMLV978U3JTkA9TUFDA2WefzVNPPcW4ceOYO3fuQfssX76cV155JXF/0aJFLFmyhP/4j//gr3/9K3/84x+55JJLpC6WSLs+fTrdf//9h3389ttv5/bbbz/sPh1Vcru65pprZAgoTbxzR6A5DRof3UTDnzZQevks9H4WdjscM2LithRWmirs9mR/jb0IZHl55n971A37T1WZZi97HoKm2UNBhgPoJUAbNb9/z5EMy4JYECIBiLZD/WZ4+DP28FOa+BvqyCtN/4dxLBJhw6svMe3ET1A5JTWF4ADmzp3Lhg0bePXVVw8KWN5++21eeeUVTjjhBI499ljWr1/PsmXL2LVrFyeffDKXXHIJf/zjH3n00UflPVqknWTqCXJmllD6/2YR3dtGw33rUFEr5c/h39GCrml4Rg38W2Oq1NfZ3/ZHjcycNh2KFh8aUFaslz0znK7bw0S5ZXYvjjMewOaPTluT/A11ae9hsUyTf/32l7Q3NXH00nNSeu6NGzeyc+fOHpcSWLt2LTNmzOC0006jsLCQE088MTEc/8gjj/DHP/4RYEDTo4VIlczJfhRp5R6bT9lXZlN37/s0PbWVok9PTmkRqtadfnTIqBlCzY0hLBQVGTRMdSiGcYghoWzXsse+LhiVlqdXlkVrQwP5ZenrYTFjUZ6/5062vruS8771PUaM69uMnsN58sknef/995k6dSoXXXTRQY+HQqGDFnGsqqriK1/5Co2NjdTW1pKbmytlI0RGkIBFJLjG5FF0wWSaHtuMUeim4LSxKTt3aF87LqXIH5M5K9y2NoeIGRp6FqyGrOsdPSzDLGDx7wFvSWdPyxBrb27CMmPkp2lISFkWd1x6AQBnXn0DE+cvTNm5N2/ezPvvvw/YuYIfr4e1fv16mpqaGD9+/EHHappGSUkJJSUlKWuPEAMlAYvoxje/HLMphP+l3fjml+MoTk1uQexAEEvXMByZM0so1BoFV3ZMz+3MYcnyIaGPa9kDBekdDgLSNiTUuH8vAMeccyEzTj41pefuWCDxE5/4RLdlK+rr61mxYgXvvfces2bNSvkaREIMFglYxEG8x5Tjf2k30fpAygIWWiPEPJn1cjPbYxgZNM36cDqGhJQaZj0sLXuhIH3DDf76eMCSpiEhM2pPN6+cenAF24E6+uijaW1tZfny5axfv57p06dTW1vLli1byM3N5bTTTmPhwoWDuninEKmUWZ8gIjOY9rcxLYVDJc6wSSTDZuNoIRPniMyZtXQ4iaRbM/UJ0WnVvBsm9r8k/kD5G+pxe324vel5bZaNHU/ZuAlsXvEGk49dlNJz67rOKaecwuTJk3n77bd5//338fl8nH/++cyaNQuHQ97+RXaRV6w4iOoIWByp+eZlhmN4lEKVZla9E2dUkZOf/mJhyUj0sGT7LKGP0zTY8Ro8c4M9e8iVG7/uctudm7jvdxZAbhk+Q8f4WM9ANBxi9bP/QDcMPLl5eHJz8fhycfvsa09uLq4cb7ceBX9DfVpL8muahsuTg9Xf6epJGDVqFBdeeOGgnV+IoSIBizhYx/t5ir7Mt+z0o2kaORk0pTkYiZFjQV4WVLmFrgHLMBsSmn85fPgP2LPKLiyXuLQB6qDdfegsWvAwu3NG4jN08gyDPIdOrmFgBNpgdz1nrH2NSLDnAnWapuPOzcXj8+Hx5dJSX8fISVMG+Yc8tFgkQu22LZxw8RfS1gYhsoUELOIgejzXxAqkppx7604/BpA3LnOmNO/Z34aORnFJdgwJGY5hGrAc95/25eOU6qySG2mDSBubP3iWKW/dxo2TxhDKHUmradIas2iNmbSaJm+1NLN3xgL+ee1VoEE4ECDc1kaoPX5payXc3kYovi3c3kZeaRkzTkptsmuyYpEI//7d/2CaMSbOX5CWNgiRTSRgEQfRc50Y+S6CGxvJmVU64POF9sVXaa7KnIBlf41dln/EiMyvwQJgdExrVgf3OgxLmmavN+TyAvaQTcP6V5iAwfkTpyVmTXX1pc0f0Y4LPZ7vk5ObR05u5kyj79De3MSWd1aw9vlnaKmt4Zzrb6RoZHrq0AiRTSRgEQfRNI3cT4ym5ZntuMbk4Tu2YkALI8YOBAnpOrojc+qd1NfZqxyPzoIqt2AXiAWwrCMkYOmB2bKXA54SynsIVgD2m4pSFe7xsUywY+1qXvrj7/HX16LpOmOPmsvZX/8vysYeXAdFCHEwCVhEj3IXVRKrC9D85Fba3tqHa0wejtIcHCU5OCu8OEpykg5itNYIsQybPtx4IIhCZU8PSzxR1Oohr+NI4fDvozmnnEMti1qvO5mqIkPapmS0Hmhg2f/ew7Z3V1I1azYnX/olxsycjTf/4FL5QohDk4BF9EjTNYoumIx3Thltb9cQ3d9OcH0DKmTnUGhOHUe5F9fIXNwTC/BMLUbP6fnl5AybRCp6njYaCcU4sLedbe/V4fE6mHHiKLz5rkH7uTq0NYexdA1HBhWyOxwjHhweKSNCPclt20Nr3qGLzDW6vYyyMmvatxmL8cRPbybU3sbZ132bqYtOkronQvSTBCzisNwTCnFPKATs/AmrPUq0pp3ofvsSqfbTvqomsX/B2ePxTCnCMcKePhoLxqc0l+VgmRaN+9up2e6ndkcLtTv8NNUGuk0GeefpHUycN4K5p1VRPohJusHWCHqWVLkFEh9yVoZ9IA+lsva9bKvsOTm1sa2NkDuHtfv386MXX6HQ5aLI46Y4x0NxTg4luT7K8vMoyMk5qET9YNq3+SMO7NnNxT/6BaMGoTicEEcSCVhE0jRNw8h1YUxy4ZlUlNgeaw7TvmIfrcv30PLsDlqe3YHmMdC9TqxQDE3TWPNWDa+8U0csbKLpGiWjfIyaUsTRp1dROjoPb4GLQEuEmu0tvPX3rWxdXYfh0Jl96mgKR3gpKMuhYIQXX6ErJd9QzfYYek529K50daT2sMQiIUaE6thR1PP6Vg7DYExLA9sLy/lQ82BZBgSAQAxojV9q0CwTdyTM5/UQPzlj8GcHdRSk27txAxUTJydmewkh+k7+esSAOQrdFJw5noIzx2NFTCK7/ET2tqGCMWKBKDW7Wxkx1cOUylwqJuRTVpWP031wsOArcFNWlcf040fy8oMf0dYUZuvqOtoaQ4kP6px8FxOPLmPukioKygYwJTlk4siwQnZZyYxBwyao3QC6AZPPsAu9pdi6tf/kaBTe4qoeH8/PyWHV+UsAuxeqLRSioa2dhrY2DrQHaAqGaAqFaTYj3K8c7AoNTa5L2djxHLX4DF5/+E+sf/Ulzr3hJkrHpG5RUSGOJBKwiJTSXQaeyUV4Jnf2wJQAM/twDofL4PQvz0rcN6MW/gNBmuuC7N3cxJZVtWx6u4bzrjua8vH9GzZyRhU5eYOfK5NymTCK1VYP6x6FrS9B9TvxIm9xrly4/N8wcvaAn+btBy8nt3kHEVcueYFaAGbOPK3X43RdJ9/rJd/rZcKIg6vY/uH5lRRYOqFIFI9rcCsda5rG6Vdey9zTz+Zfv/0l//rtL/nCz+6UPBYh+iFz5pkKcQiGU6eowsf42aWc+OnJXHrrcRSVe3ntkU39Ol8wEsNrZk+V267S9jGnFFSvgie+Ar+aDi/dApoOJ30TvvQvuLEavvIyFI6FJ7484KeLRcMcu/1JNGWiNJ2gK4+3Zl6Bw+ke0HkjZoyow8njvv/f3p1HR1Vnix7/1pCqVIaqzCEhITEkjBKQgBABEUSkEQTtXiqNYrd0t7aCvR7aCpduEe5F6WfbXt7lOjy9raLvirYIikLTIAhBRAJhSpQpjCEJGchYSVVq+L0/SnKlCRnIVKnan7VqLZI6dWqftak6O7/zO/sXQ/LXeazJzml3rK0Rk5zCqHvuo/Tsac4c6pr3FMLXyAiL6HEMgXrSJyay9e3vsFbZCba07SR24aIVHRrCI6VguYLLAbtegfztUFMIAcEQ1gfM8XBhPxQdhPBkmPQ8DPs5BEVc+freGXDr0/DxL8FaBsHX33SwtOwMcSgabl3I8Jvuas9RXcGg0/NJUjhZ5wt4GTPVDV13G/TllZk/eXEJT334eZe9rxC+QkZYRI/UZ3AEOr2Wbe9+z6Uia5tee7HEs85MVFTP6MFymVtp6NQrCV8sgB3/G0JjYcA0SMoE5YLz30JIDPz8I5h/AG6Zd3Wxcpm1FHQGMLavw2xl2WkALNEd31RtdGoKmb3jAUg0d1335QFjxnfZewnhi2SERfRIphADUx69kR3/fYwPln5LaGQgUQkh9O4XTtrI2GZ7uVwq8xQs7WkaV21zcKrUSkFFHQE6LcmRwaTFhKBtR0fg5lxuyd9pBct3n0LOapi+EjJ+cf37ubAfYm8Effsu3dSVnwUgJiq5Xfu5lnOVVYCOGyLDOmX/TdEbDNzx63lseXMVdVWVBFm67r2F8AVSsIgeK3lIFInLIjh1qJSSszWUnqtm97qTZG88zc+eGUFYbNMFSdUlGwC9rtHMrimFlfXsO1tB9ulLfHu6nOMXa6/aJikyiDmZyTw0OglDBy9D4Faey0Gajr4oZK/xFCpblsDge2D4w+3b37k90H9qu8NyVp6lxBBJTGDnjIKdr7GCJoTkqKsn5XYme30dOr2+ybWQhBDNk0+N6NF0AVrSRsSSNsLTsL2uuoGPXsjm4NZz3DZ7QJOvqa20Y9Mogk1N3yGilOKbU+VsOFRIhdXB4YJKCqs8Rc4NUcGMuiGCR2/tS/9eoSSGB+F0u/m+qIa1OQW8sPF7Pso+z6sPDqdvdMfd3quU6rhSxWGDwhzIWw8H/xscdTB8Dkx9qX1DOEpBTTEERbb6JWeLTlBvt6IPMKENMKE3mNAHmAgoPkxZSAIx1x9NswrrbRBs5rXdewgNMBBqDCDUaMRsNGIxBWIxmQgLMhESGNhhjeaUUhz6xxf0yxxHYEjPWMNKCG8iBYvwKUFmA32HR3PqQKnnJN/ECbi+xoFN3/SJ2Wp38tv/l8PO46XcEBVMZLCBnwyJY2RyBBlJ4USHNn2pY2yakbFpUfx6XArzP8hh6sosxqRGMbxPGEMSwogIMpAQbiIsKOC6bml1K8+Es3adOsvz4fP/5RkFcdkhKApGPQojfgmWa7e8bzWNxjNKs/MlSBwJKbc1u3nppQskvjESbRPrI8UDO2/9U/tjuobYQE8e/6RCoQHPo8YBOIAfjZ4pNwaHA51yE2Gz8sVtI+kVdp1rAClFTXkZ0X2S2xe8EH5KChbhc5KHRHF4WwGl52qISbp6UqWjzon7Gm35V20/SfbpS7w5ZwSTBsa0ubgYFG/m03ljWf3NGb7JL+e1r/KxNrganzfotESFGEiICCIxPIi02BDG9I1iSELzJ0GFQtGOAZCiw/DePRBogTuWeSbUxt7oafbWke7+P547jD6dB/OyIeDazf0qLhUQjSJn/ApCI5NwO20ohw3lqMet1TP65p93bGw/8i+TxvMvQH2Dnao6G5V1dVTV26i22ai226lpcFDT0ECtw0mtcpLl1HLcEkWZ1XrdBYtGqyV5WAYn9u5m5N0/7dgDEsIPSMEifE58vzBCIwPZ/GYuqRkxRMSHEGQ2EGQ2YI424bK50BiaHqvY9n0J04fGccega60J3LIQo57Hb0vl8dtSaXC6Ka21U15rp6CintIaOxerbZyvqOdkaS2bcotYseko6QkWfnFLMncPjUevuzq2y51+r7tg2boETOHwyGYIbv0lmzbTG+EnL8Grozy3Rw+49nwWm7UCgNgBE+kd17/zYmqGyWDEZDC2WIT8x45dLHdDYnhYu97vhqEZbHvnDSqKCwnvFd+ufQnhb6RgET5Hp9My7Ymh7P38FMf2FGOt+p9eG3qDFnODm6IIHQ6Xm4AfFQclNTaOXazhN7emdFgsBr2W3mEmeoeZSE8Iu+p5p8vNjuOlrP7mLAs+OsTKL0+w4I5+zBjW+4rt2rWG0KVTcGoH3PVy5xYrl0X/UHx8v6HZgkVjrwKgrq6q82Nqp4v1dgK0BixB7ZsEPGj8RLI3rOWbjz9g6rynOig6IfyDFCzCJ0XEBzPlN0MAcNhd1FU3UFfdQP6BEg5kXeBIfT0j/m0rkwbGMnlwLEa9lv/adRqLKYDbB3bWVM+r6XVabh8Yy+0DY8m9UMW/bz3B79YcpNbuZPao/1lzxv1DxaJFwdlvoOKMp/19zKDmh12sZbDmQbD0hvT7OvlofnA5nhaGg/oPnkTxlzFU7ngF+n7QBYFdv7IGByHa+nbvxxBoYuDYCRzaugm324W2oy/JCeHDpGARPi/AqPOs9hxtIq6vhTE/TWVCYTWb84rZlFvM2pwCAGLNRl76WTphQd2zxtCNvS289fAInvzgAP+16/QVBYsCdBpF+qFlcOhHLwrrA/3vghvGeTrVVhd6blXWaMBWBQfe87TQ/+XfwdD627jbLfZGTwO5ZhiCIzl102PcvGc5Z84dJrlP+9cf6izlLoXZ3TFdcW8YlsG36z7k4qmTxKV2z6UwIXoiKViE39FoNNzY28KNvS08Nbk/58o9jeQSI0xesSjdmNRIPjtUSGFlPfFhJpRSfLzvPGmuwaQl9SZm8lPQawic+waOboS8dfDta54X600QaAblBo0O0h+A8c+0q03+dYnuD8WHW9xs+ITfUnj4bazrn0TN+xKNl444XFIaLMrV8oat4HJ6WvTr9J278KIQvkYKFuH3+kR6V4v+yYN68e9bTzDjP7/mZxkJnC23svFIMT8f9QZL7x4Ml+fdpE7yPKb++YeW+AGeibVeUHTRfyqsnQsX8yD22mt1BxqDKJ/wPDd9MZdvd/xfRk34bRcG2XpVWj19cTS7jcNm4+T+b6koLGDvpx+TfvsU0m+/k4jeiWh1OpRSlJzOJ+uDdwkJj5Dbm4VoIylYhPAy4cEG1j0+hj//4xh/23cenVbDygeGXTURt5FW61n/x5sMvBsiUuDTJ2D2x1eN8FSXnCT/0GfoT25hUOk+AFwlR7sj0lapCTBibXDwSc4hTAF6THo9JkMApoAATAYD6lIZX636MzXlpQSHheNyODjw9w0c+PsGNFotxqBg7HVWlNuNJbYXdz+1GE0HNaQTwl9olGrX/Qdeobq6GovFQlVVFeYuXMxMCNGMwgPw/k8BDdy5nNLAGIpzPyf89Jck1J6hQaMnL3I4NSmT6JM+neSEQd0d8TUN3vAV5SFhzW6zaMffmPPo44THeQpLW20tpWdPUV5wHnt9HcagYCzRMSSl34RW552XvoToam05f0vBIoToPLUlsPFpz+KKQLEhkv0xYzANmMKg9J/Qy3yNVZ+9THV9PcWVVdgcDuodDuocTs+/nU4er/R8hRbceiN6WSNIiDZpy/lbPl1CiM4TEgP3rabwzD4WHzvP3wOSUBotUehxH75Ag7sAnUZDsE6LTqOhT6CBX/SO4idRFvSdtPL19TCbTJhNTXftXbn3KKMswVKsCNHJ5BMmhOh08ckjeDt5BJUOJ9su1XCm3o4ODUatBqdSWF1unEqRXWXl13lniDZ4vpq2jxxAlMF7v6aUUlQ4nEQEeG+MQviKNs36eu2110hPT8dsNmM2m8nMzGTTpk2NzxcXF/PQQw/Rq1cvgoODGT58OGvXrm12n88//zwajeaKx4ABTa+yK4To2cIC9NwbG86C5F78LjmWx/rEMC8plmdT4ljcN571w9P4x4h+GDQaShucTMo+hs3l7u6wr6nQ7qCkwcmwUO+600wIX9SmgiUhIYEVK1awf/9+9u3bx8SJE5kxYwZ5eXkAzJkzh2PHjvHZZ59x5MgR7r33Xu677z4OHDjQ7H4HDx5MUVFR42PXrl3Xf0RCiB4tPTSI/bcM5oP0FCqcTp47eQFvnWr3YfElDBoNIyxd2JRPCD/VpoJl+vTpTJ06lbS0NPr168fy5csJCQlhz549AOzevZv58+dz8803k5KSwh/+8AfCwsLYv39/s/vV6/X06tWr8REV1cVNroQQXmdCpJl/S+vN6sJyXj5zsbvDadKGkkrujQ336stWQviK624E4HK5WLNmDVarlczMTABuueUWPvzwQy5duoTb7WbNmjXYbDZuu+22Zvd14sQJ4uPjSUlJYfbs2Zw7d67Z7e12O9XV1Vc8hBC+56H4KBanxPHnM8WsOFXkdSMtlU4X8YHSsVaIrtDmPwuOHDlCZmYmNpuNkJAQ1q1bx6BBnv4JH330Effffz+RkZHo9XqCgoJYt24dqamp19zfqFGjeOedd+jfvz9FRUUsXbqUcePGkZubS2hoaJOvefHFF1m6dGlbQxdC9EDzk2LRajT8a34hx6w2nk+NJ8lk7O6wcLgVNU4XgdIATogu0eY+LA0NDZw7d46qqio+/vhj3nrrLXbs2MGgQYOYP38+e/fu5YUXXiAqKor169fzyiuvkJWVxZAhQ1q1/8rKSpKSkvjLX/7C3Llzm9zGbrdjt9sbf66uriYxMVH6sAjhwz4vqWTRiQLKGpyMDw/lwfhIpnTj7c9/LSjlDycu8OXI/gwMafqWZyFE87q0cdykSZPo27cvzzzzDKmpqeTm5jJ48OArnk9NTeX1119v9T5HjhzJpEmTePHFF1u1vTSOE8I/WF0uNpRU8n5hOfuq60gLMvLB0L4kBHb9Ctv3HDhBqE7H6vSULn9vIXxFW87f7R7LdLvd2O126uo8K95q/2l4VKfT4Xa3/rbE2tpa8vPziYuLa29oQggfE6zT8UBcJJ9n9GPziH7Uudw8e6ygy+O4YGtgb5WViZHyB5IQXaVNBcuiRYvYuXMnZ86c4ciRIyxatIivvvqK2bNnM2DAAFJTU3n00UfZu3cv+fn5vPzyy2zZsoWZM2c27uP2229n1apVjT8//fTT7NixgzNnzrB7927uuecedDods2bN6rCDFEL4nqGhQfwuKZavKqqpdrq67H2tThcLjp4n6oeeMkKIrtGmSbclJSXMmTOHoqIiLBYL6enpbN68mTvuuAOAjRs3snDhQqZPn05tbS2pqam8++67TJ06tXEf+fn5lJWVNf5cUFDArFmzKC8vJzo6mrFjx7Jnzx6io6M76BCFEL7qlvAQXAoOVtdxa0TTk/RbSynFUauNXRW1lDY4GGEJxqEUJQ1OSuwOShuc5NfbOFxTj1MpVg9JwayXRQyF6Cqy+KEQosdyK8XgXbnMiovkudT4Nr3W5nJz1Gojt7ae3ZW17KqooaTBiUGjwazXUeZwAqDXQIwhgGiDnsRAA0NDg5gRE0YfL7hTSYieThY/FEL4Ba1Gw/1xEbx9oZRHEqKanXxb73KTXWUlq6KGXRW1HK6tw6U818WHhJq4r1cEt4aHMtISTKBWw3lbAyF6HWF6HVqN9yzEKIS/koJFCNGj/SYhmr8VVzBl33Eeio9kQEggITodARoNFxscnKqzk11lJbvait2tiArQMzY8hAfiIhgSamJAsIkg3dXT+WQERQjvIgWLEKJHiw80sH1kf/50uoi3Ckqp+afFEqMNem4KDWJxShzjwkMZEByIRkZMhOhxZA6LEMJnKKWodrqwutw4lCLKoCdYJxNjhfBWModFCOGXNBoNlgA9FlneRwifI4tgCCGEEMLrScEihBBCCK8nBYsQQgghvJ4ULEIIIYTwelKwCCGEEMLrScEihBBCCK8nBYsQQgghvJ4ULEIIIYTwelKwCCGEEMLrScEihBBCCK8nBYsQQgghvJ4ULEIIIYTwelKwCCGEEMLr+cRqzUopwLNMtRBCCCF6hsvn7cvn8eb4RMFSU1MDQGJiYjdHIoQQQoi2qqmpwWKxNLuNRrWmrPFybrebwsJCQkND0Wg0VFdXk5iYyPnz5zGbzd0dnmiC5Mj7SY68n+TIu0l+WqaUoqamhvj4eLTa5mep+MQIi1arJSEh4arfm81m+U/i5SRH3k9y5P0kR95N8tO8lkZWLpNJt0IIIYTwelKwCCGEEMLr+WTBYjQaWbJkCUajsbtDEdcgOfJ+kiPvJznybpKfjuUTk26FEEII4dt8coRFCCGEEL5FChYhhBBCeD0pWIQQQgjh9aRgEUIIIYTX87mC5fjx48yYMYOoqCjMZjNjx45l+/btV2yj0WiueqxZs6abIvY/rcnRZeXl5SQkJKDRaKisrOzaQP1YSzkqLy9nypQpxMfHYzQaSUxMZN68ebKeVxdpKT+HDh1i1qxZJCYmYjKZGDhwICtXruzGiP1Pa77nnnzySTIyMjAajQwbNqx7Au1BfK5gmTZtGk6nk23btrF//36GDh3KtGnTKC4uvmK7t99+m6KiosbHzJkzuydgP9TaHAHMnTuX9PT0bojSv7WUI61Wy4wZM/jss884fvw477zzDlu3buWxxx7r5sj9Q0v52b9/PzExMbz//vvk5eWxePFiFi1axKpVq7o5cv/R2u+5Rx55hPvvv7+bouxhlA8pLS1VgNq5c2fj76qrqxWgtmzZ0vg7QK1bt64bIhStzZFSSr366qtq/Pjx6ssvv1SAqqio6OJo/VNbcvRjK1euVAkJCV0Rol+73vw8/vjjasKECV0Rot9ra46WLFmihg4d2oUR9kw+NcISGRlJ//79Wb16NVarFafTyRtvvEFMTAwZGRlXbPvEE08QFRXFzTffzF//+tdWLW0t2q+1Ofruu+9YtmwZq1evbnFBLNGx2vI5uqywsJBPPvmE8ePHd3G0/ud68gNQVVVFREREF0bqv643R6IF3V0xdbTz58+rjIwMpdFolE6nU3FxcSonJ+eKbZYtW6Z27dqlcnJy1IoVK5TRaFQrV67spoj9T0s5stlsKj09Xb333ntKKaW2b98uIyxdrDWfI6WUeuCBB5TJZFKAmj59uqqvr++GaP1Pa/Nz2ddff630er3avHlzF0bp39qSIxlhaZ0e8afrwoULm5wo++PH0aNHUUrxxBNPEBMTQ1ZWFnv37mXmzJlMnz6doqKixv398Y9/ZMyYMdx00008++yzPPPMM7z00kvdeIQ9X0fmaNGiRQwcOJAHH3ywm4/Kt3T05wjglVdeIScnh08//ZT8/HwWLFjQTUfX83VGfgByc3OZMWMGS5YsYfLkyd1wZL6js3IkWqdHtOYvLS2lvLy82W1SUlLIyspi8uTJVFRUXLGUd1paGnPnzmXhwoVNvvaLL75g2rRp2Gw2WfPhOnVkjoYNG8aRI0fQaDQAKKVwu93odDoWL17M0qVLO/VYfFVnf4527drFuHHjKCwsJC4urkNj9wedkZ/vvvuOCRMm8Ktf/Yrly5d3Wuz+orM+Q88//zzr16/n4MGDnRG2z9B3dwCtER0dTXR0dIvb1dXVAVw150Gr1eJ2u6/5uoMHDxIeHi7FSjt0ZI7Wrl1LfX1943PZ2dk88sgjZGVl0bdv3w6M2r909ufo8nN2u70dUfqvjs5PXl4eEydO5OGHH5ZipYN09mdINK9HFCytlZmZSXh4OA8//DDPPfccJpOJN998k9OnT3PXXXcBsGHDBi5evMjo0aMJDAxky5YtvPDCCzz99NPdHL1/aE2O/rkoKSsrA2DgwIGEhYV1dch+pzU52rhxIxcvXmTkyJGEhISQl5fH73//e8aMGUNycnL3HoCPa01+cnNzmThxInfeeScLFixovJVWp9O16oQr2qc1OQI4efIktbW1FBcXU19f3zjCMmjQIAwGQzdF78W6b/pM58jOzlaTJ09WERERKjQ0VI0ePVpt3Lix8flNmzapYcOGqZCQEBUcHKyGDh2qXn/9deVyuboxav/SUo7+mUy67Xot5Wjbtm0qMzNTWSwWFRgYqNLS0tSzzz4rOeoiLeVnyZIlCrjqkZSU1H1B+5nWfM+NHz++yTydPn26e4L2cj1iDosQQggh/FuPuEtICCGEEP5NChYhhBBCeD0pWIQQQgjh9aRgEUIIIYTXk4JFCCGEEF5PChYhhBBCeD0pWIQQQgjh9aRgEUIIIYTXk4JFCCGEEF5PChYhhBBCeD0pWIQQQgjh9aRgEUIIIYTX+/884/V+iZDQBQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "simpleMAP = MAP\n",
    "if simpleMAP.geom_type != dummyPoly.geom_type :\n",
    "    areas = [geo.area for geo in simpleMAP.geoms]\n",
    "    simpleMAP = simpleMAP.geoms[areas.index(np.max(areas))]\n",
    "borderCounties = list()  #We will later connect across Sandusky Bay\n",
    "barredCounties = {71}  #we fused east of Port Clinton, but Sandusky is still NOT allowed to be a border county in this one\n",
    "for c in range(nCounties):\n",
    "    if countyGeom[c].intersects(simpleMAP.exterior) and c not in barredCounties:\n",
    "        borderCounties.append(c)\n",
    "        plotPoly(countyGeom[c])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "b3da9300-1343-47e9-9232-01e922b83f15",
   "metadata": {},
   "outputs": [],
   "source": [
    "countyUnitList = [list() for c in range(nCounties) ]\n",
    "for u in range(nUnits):\n",
    "    countyUnitList[ countyNo[unitTractList[u][0]] ].append(u)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "d09f8d23-ea8c-4f0f-932d-41fde73508d1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "borderUnits = list()\n",
    "for c in borderCounties:\n",
    "    for u in countyUnitList[c]:\n",
    "        if unitGeom[u].intersects(simpleMAP.exterior) and c not in barredCounties:\n",
    "            borderUnits.append(u)\n",
    "            plotPoly(unitGeom[u])\n",
    "plt.show()\n",
    "onBorder = [0]*nUnits\n",
    "for u in range(nUnits):\n",
    "    if u in borderUnits:\n",
    "        onBorder[u] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "a97b8194-df4b-405d-83fb-ab011bad9c20",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Check: any extra border munis near Sandusky?\n"
     ]
    }
   ],
   "source": [
    "for u in range(nUnits):\n",
    "    if onBorder[u] == 1 and unitGeom[u].centroid.y > 41 and unitGeom[u].centroid.x < -82.5 and unitGeom[u].centroid.x > -83.2:\n",
    "        plotPoly(unitGeom[u])\n",
    "        plotCenter(u,unitGeom[u])\n",
    "plt.show()\n",
    "print(\"Check: any extra border munis near Sandusky?\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "dbae70fc-5306-48ef-8474-77e56f1926ee",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dropping units {1074} from the border set; they only border Sandusky Bay, not the true exterior\n",
      "Making the neighbor bridge from Danbury to Bay View\n"
     ]
    }
   ],
   "source": [
    "falseBorderUset = {1075}\n",
    "print(\"dropping units\",falseBorderUset,\"from the border set; they only border Sandusky Bay, not the true exterior\")\n",
    "borderSet = set(borderUnits).difference(falseBorderUset)\n",
    "borderUnits = list(borderSet)\n",
    "print(\"Making the neighbor bridge from Danbury to Bay View\")\n",
    "unitNbrs[1081].append(1755)\n",
    "unitNbrs[1755].append(1081)\n",
    "\n",
    "isBorder = [0]*nUnits\n",
    "for u in range(nUnits):\n",
    "    if u in borderUnits:\n",
    "        isBorder[u] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "febb7f03-b536-4d17-8d61-ea4e9599af7f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Make a tentative set / list of border units. Numbered units have zero nonborder neighbors; will be surrounded next block\n",
      "'pop' shows pop/aDP for pop/aDP > 0.5 in a border unit\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Make a tentative set / list of border units. Numbered units have zero nonborder neighbors; will be surrounded next block\")\n",
    "print(\"'pop' shows pop/aDP for pop/aDP > 0.5 in a border unit\")\n",
    "\n",
    "surroundedBorderUnits = list()\n",
    "for u in borderUnits:\n",
    "    plotPoly(unitGeom[u])\n",
    "    if len(set(unitNbrs[u]).difference(set(borderUnits)) ) == 0:\n",
    "        plotCenter(u,unitGeom[u],9)\n",
    "        surroundedBorderUnits.append(u)\n",
    "    if unitPop[u] > 0.35 * aDP:\n",
    "        plotCenter(\"pop\"+str(r3(unitPop[u]/aDP)),unitGeom[u],8)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "1be34afe-7873-48d9-9b13-e8b48caee20b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "a couple of these are big corners, not truly surrounded. Add a cattycorner neighbor\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cornerUnitSet = set() \n",
    "cornerUs, cornerCattys = list(), list()\n",
    "print(\"a couple of these are big corners, not truly surrounded. Add a cattycorner neighbor\")\n",
    "for u in surroundedBorderUnits:\n",
    "    for uu in range(nUnits):\n",
    "        if uu not in unitNbrs[u] and uu != u and unitGeom[u].intersects(unitGeom[uu]):\n",
    "            cornerUs.append(u)\n",
    "            cornerCattys.append(uu)\n",
    "            #unitNbrs[u].append(uu)  #this works as if a tiny connection existed across the four-square\n",
    "            #unitNbrs[uu].append(u)  #wait till next loop after confirming\n",
    "            plotPoly(unitGeom[uu])\n",
    "            plotCenter(\"catty\"+str(uu),unitGeom[uu])\n",
    "            cornerUnitSet.add(u)  \n",
    "            plotPoly(unitGeom[u],2)\n",
    "            plotCenter(\"corner\"+str(u),unitGeom[u])\n",
    "            for uuu in unitNbrs[u]:\n",
    "                plotPoly(unitGeom[uuu], 0.3)\n",
    "            plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "9f7d4284-9e21-4db9-a24a-853efa954a4a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "we will implement this one.  Sometimes we find a catty that is really a fragmented VTD\n",
      "creating neighbor link for 806 and 1244\n"
     ]
    }
   ],
   "source": [
    "print(\"we will implement this one.  Sometimes we find a catty that is really a fragmented VTD\")\n",
    "for i, u in enumerate( [cornerUs[0] ] ) : #,cornerUs[1] ] ):\n",
    "    uu = cornerCattys[i]\n",
    "    unitNbrs[u].append(uu)\n",
    "    unitNbrs[uu].append(u)\n",
    "    print(\"creating neighbor link for\",u,\"and\",uu)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "31e63dd6-b679-4261-a80c-1cdd42054c53",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Try again after assigning catty nbrs. Numbered units have zero nonborder neighbors; will be surrounded next block\n",
      "'pop' shows pop/aDP for pop/aDP > 0.5 in a border unit\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Try again after assigning catty nbrs. Numbered units have zero nonborder neighbors; will be surrounded next block\")\n",
    "print(\"'pop' shows pop/aDP for pop/aDP > 0.5 in a border unit\")\n",
    "\n",
    "surroundedBorderUnits = list()\n",
    "for u in borderUnits:\n",
    "    plotPoly(unitGeom[u])\n",
    "    if len(set(unitNbrs[u]).difference(set(borderUnits)) ) == 0:\n",
    "        plotCenter(u,unitGeom[u],9)\n",
    "        surroundedBorderUnits.append(u)\n",
    "    if unitPop[u] > 0.35 * aDP:\n",
    "        plotCenter(\"pop\"+str(r3(unitPop[u]/aDP)),unitGeom[u],8)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "0f99211c-4b63-45af-b6df-af41b4627c7a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "check for double surrounds\n"
     ]
    }
   ],
   "source": [
    "print(\"check for double surrounds\")\n",
    "doubleSurrounds = list()\n",
    "for u in surroundedBorderUnits:\n",
    "    candidates = list()\n",
    "    for uu in set(unitNbrs[u]).difference(set(surroundedBorderUnits)):\n",
    "        candidates.append(uu)\n",
    "    if len(candidates) == 0:\n",
    "        print(u,\"is surrounded by surroundees\")\n",
    "        doubleSurrounds.append(u)\n",
    "        plotPoly(unitGeom[u],2)\n",
    "        for uu in unitNbrs[u]:\n",
    "            plotPoly(unitGeom[uu],0.8)\n",
    "            plotCenter(uu,unitGeom[uu])\n",
    "            for uuu in unitNbrs[uu]:\n",
    "                plotPoly(unitGeom[uuu],0.2)\n",
    "    plt.show()\n",
    "#    else:\n",
    "#        uuDists = [unitCP[u].distance(unitCP[uu]) for uu in candidates]\n",
    "#        uuu = candidates[uuDists.index(np.min(uuDists)) ]\n",
    "#        print(\"we will collapse unit\",u,\"into unit\",uuu)\n",
    "#        surrounderBorderUnits.append(uuu)\n",
    "# plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "6cccad72-2638-4464-95af-92b00147bcfb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "we now have 5710 units\n"
     ]
    }
   ],
   "source": [
    "print(\"we now have\",nUnits,\"units\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "3c063f00-b4ec-4242-8563-e7913b29674f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "flagging border-stringy near Sandusky.  May want to avoid surrounding these\n"
     ]
    },
    {
     "data": {
      "image/png": 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EeUiTkBAXOZ130eHDmlmPIcBy3nM0TaPndY0B+PaltWz76ygOm7PM17RZHaz//SAoCGsoI4KEEFVPU6f/1LrIZWVl4efnR2ZmJr6+vjUdjhDVqjA5F2d2ITpPA8Ywr1Kbg05LO5rDn5/vIPVIDtHNAxg8rq17xE9JcjOsfD95HXlZhXQcEEu34Y0q4xaEEPVUWZ/f0iQkRB1givCCCK9ynxfUwJsbnu7CrjUpLJ6xnfTkXIKjSl6o8NjBLBZ+uhUFjJrUvdwji4QQoqIkYRFCUJBrQ2fQ8Av1LPGYwgI7f87cjsGkZ+C9bSRZEUJUK0lYhBAk7ckgIt4Po0lf7P7jh7JY+Ok28rIKGfFoR0KiS66FEUKIqiAJixCCvEwrfiHF164UFtj5+a1/8Av1ZOgD7fA/Ty2MEEJUFRklJEQ9V5hv52RSLj5BxY8s+r8f9uJ0KAbf10aSFSFEjZGERYh6bulXO1FAy16R5+w7diCL7SuT6HldY7xLGSothBBVSRIWIeoxp1Oxd+NxugxpiE9g0YQk5UAmi2ZsIyjKm5aXNqihCIUQwkX6sAhRj+l0Gjq9ht5QdLbbdb8dYO2vBwiJ9uGKO1ui01VsNlwhhKgskrAIUY+dOJyN067wDXINUVZKsXX5Udb+coDOg+PoMiQOXSkTyQkhRHWQhEWIemzdbwfwDbbgFWBm1+pkDmxOY9/G47TtG8UlwxqiaVKzIoSoHSRhEaIeSzmQRX5WId/9dx0AviEeXH5bC1r0iKjhyIQQoihJWISox7pdFc/J5FxiWwcRFueLyaP4fxI+/Ws/7y/dy6oJ/bAYi59cTgghqpIkLJXIkWXFnmHFFO0jVeniolDcUObivPzbDgByrXZJWIQQNUISlguglAIFaICC1C+2YzuSgyHEA68u4Xh2DEXvbarpMIW4YNteHMDagycJ8jbXdChCiHpKEpYyOPHxZmwpuSinAqdyf8V51kGnkha/ofEUJmaT+cdBMv84iEfLILy6hGNu7I8mQ0PFRcrLbKBvs9CaDkMIUY9JwlIG1kNZWJoFYo7zBZ3mSjxOfz2VqCilMARYsDQNAMCRayPvn+Pkrksh9bOt6APMeHUOx6tzGHo/+StVCCGEKA9JWMpCKSzNAvDuWvaRE3ovIz69GuDdM5LCxGxy16aQvSyRrMWHsDQNwNzIH3NDP4yRXmgyz4UQQghxXpKwlMXpfioVoGka5hhfzDG+OIfGk7fpBPmbTpC16BDK5kQz6TDF+GKO88UU54cpxgdHViGZv+zDfrIAS7NAPFoGYYr1RdNLk5IQQoj6SRKWUpzuWFsZo350FgPeXSPw7hqBsjspTMqh8EAW1oOZZP9fEmrxYTjVzKT3M2OO9yNv0wlyVh5F52nA3CQAnaXoCA2dhwFjAx9M0T7o/UwyOkkIIUSdJAlLadSpr5WcB2gGnbvmxad3FMqpsB/Pw3ogE2Vz4tUtAp1Jj3IqbEdzyN+ehnVfBnaHKlKOM7sQx7IjAOi8jZhifPHuEYmlsX/lBiyEEELUIElYSuNOWKq25kLTaRjDvTCGe52z3RTtqkEpiSOrkMIj2RQmZlOw6ySpn27B3Ngf3ytjMcf4VmncQgghRHWQhKU06lTGUotbWvS+JjxaBuHRMgjfK2Mp2J5G5sJDnPhgE5YWgfheGYcpwqv0goQQQohaShKW0pzOVy6SviGapuHRKhhLiyDyN58gc9Ehjr+zEY+2IfgNiMMQaKnpEIUQQohyk/G0pVAXQQ1LcTSdhmf7UMIf6YT/iMYUHsjk2FsbyF6eiHI4Sy9ACCGEqEWkhqU07oTlIstYTtH0OrwvicCzXShZiw6RueAgef+cwP+axtK/RQghxEVDalhKU0WjhKqbzqzHf2g8ofd3AL3GiQ83kf7zXpwF9poOTQghhCiVJCylcV7cNSz/ZmrgTejY9vgNiSdvwzFS3txA3pYTZ5q+hBBCiFpIEpZSXOQtQsXS9Bo+vRoQ9khnTFHenPx6J+nf70bZpW+LEEKI2umCEpYpU6agaRrjx493b/v444/p06cPvr6+aJpGRkZGmco6evQot9xyC0FBQXh4eNCmTRvWr19/IeFVjtMZSx1cadngbybotpYE3NCUvE0nOPHpFhy5tpoOSwghhDhHhROWdevW8dFHH9G2bdsi2/Py8hg4cCBPP/10mctKT0+nZ8+eGI1G5s+fz/bt23nzzTcJCAioaHiVp470YSmJpml4dQwj5O422E/kcfyDBGwn8mo6LCGEEKKICo0SysnJYdSoUXzyySe8/PLLRfadrm1ZtmxZmct79dVXiY6OZsaMGe5tDRs2rEhola+aZrqtaeY4P0LHtif1820cf38TQbe2wNLIv6bDEkIIIYAK1rCMGzeOIUOG0L9//0oJYt68eXTu3Jnrr7+e0NBQOnTowCeffHLec6xWK1lZWUVeVeJUk1Adz1cAMAR5EHpfe0zR3qRO30ruupSaDkkIIYQAKpCwzJ49m40bNzJ58uRKC2L//v18+OGHNGnShD/++IP77ruPBx98kM8//7zEcyZPnoyfn5/7FR0dXWnxnE3VkxqW03QeBoJvb4VXlzDS5+whc/4BGUEkhBCixpWrSSgxMZGHHnqIRYsWYbFU3hTvTqeTzp0788orrwDQoUMHtm7dyrRp0xg9enSx50yYMIFHHnnE/TkrK6tqkpaLdKbbC6HpdfgPb4wh2IPM3w6g8zbhc2mDmg5LCCFEPVauhGXDhg0cP36cjh07urc5HA5WrFjBe++9h9VqRa/XlzuIiIgIWrZsWWRbixYtmDNnTonnmM1mzGZzua9VbvWshuU0TdPwuTQKR1YhmQsOYG7oiymq5BWjhRBCiKpUroSlX79+bNmypci2O+64g+bNm/Pkk09WKFkB6NmzJ7t27Sqybffu3cTGxlaovEpVD2tYzuY3IA7r/kxOfrOT0Ac7oDPLag5CCCGqX7n6sPj4+NC6desiLy8vL4KCgmjdujUAKSkpJCQksHfvXgC2bNlCQkICJ0+edJfTr18/3nvvPffnhx9+mNWrV/PKK6+wd+9eZs2axccff8y4ceMq4x4viLrIVmuubJpBR+DI5jiybWT8vK+mwxFCCFFPVfpMt9OmTaNDhw7cfffdAFx22WV06NCBefPmuY/Zt28fqamp7s9dunThp59+4ptvvqF169a89NJLTJ06lVGjRlV2eOV3emr+ejwnsDHYA//hjcjbeJy8hOM1HY4QQoh6SFN1ZAhIVlYWfn5+ZGZm4utbeasQ247lcuytjYTc1w5zbP1e3Th1xlacBQ5C72tX06EIIYSoI8r6/K7H9QZlVMdnui0Pc5MACo/myJpDQgghqp0kLKWo731YzmaK8QG7E1tKbk2HIiqZUors7O0opbDZslBKklIhRO0iQz5KU89HCZ3NFOmNZtGTveIIgSObSxJXB9hsmWRnb2X7jiewWlNw/aIrGsY9QHz8+BqOTgghzpCEpTT1dB6W4mgGHQEjmnDym53kNkrBu2tETYckKiArazPHjv1Katoy8vKKjvzy9WlDVvZmCqyyLIMQonaRJqHSVEINy4oVKxg2bBiRkZFomsbcuXP/dQnF888/T0REBB4eHvTv3589e/a49y9btgxN04p9rVu3DoCJEycWu9/Ly6vigRfDs10IXl3DyfhlH4VJOZVatqhaSimOHv2GdeuvJeXYL/j7daJVy//RresiLu+7h36X76NLl58IDR1CWtoybLaMmg5ZCCHcJGEpzel8RVfxjCU3N5d27drx/vvvF7v/tdde45133mHatGmsWbMGLy8vBgwYQEFBAQA9evQgOTm5yOuuu+6iYcOGdO7cGYDHHnvsnGNatmzJ9ddfX+G4S+I/NB5jiCcnZ+3EabVXevmi8qWkzGPN2kHs3PUsUQ1G0avnSlq0mEx4+NV4ecWjaWf+KWja5Bns9iyOHPmyBiMWQoiipEmoFKoSalgGDRrEoEGDSix/6tSpPPvss1x99dUAfPHFF4SFhTF37lxuuukmTCYT4eHh7nNsNhs///wzDzzwgLsfibe3N97e3u5jNm3axPbt25k2bVrFAy+BZtQTeHNzjr+bQMZPewm4sZn0Z6nF0jPWsW37wwQF9aVJk2cJDOh53p+X2RxGgwajOHDwAwIDe+Hn16EaoxVCiOJJDUtpqrgPy4EDB0hJSaF///7ubX5+fnTt2pVVq1YVe868efNIS0vjjjvuKLHcTz/9lKZNm3LppZdWeswAxhBPAq5pTF7CCfLWH6uSa4jKkZL8Ix6WGNq1/YSgwF5lSi4bN3oMX982bN5yHzZbVjVEKYQQ5ycJS2mqeJRQSoqrc2NYWFiR7WFhYe59/zZ9+nQGDBhAVFRUsfsLCgr4+uuvGTNmTOUG+y+e7UPx6hJO+s/7sGdYq/RaomKSk38kKfk7IiKvK1ctmE5npk3rd7Hbs0lK+qYKIxRCiLKRhKU0p6ejqCVNHkeOHOGPP/44bzLy008/kZ2dzejRo6s8Hu/LGoDdiT0tv8qvJconO3sHO3ZOIDLiBuJix5b7fLM5jODgyzmaNBunU/oqCSFqliQspTjdh6Wq8pXTfVOOHSvarHLs2LEi/VZOmzFjBkFBQVx11VUllvnpp58ydOjQc2ptqpL0YaldnE4bO3Y8iadnPM2avVjhn09c3Djy8xNJTPyskiMUQojykYSlNFXch6Vhw4aEh4fz559/urdlZWWxZs0aunfvXjQUpZgxYwa33XYbRqOx2PIOHDjA0qVLq7w56ExQoFDym1TLpKYtITtnGy1bvIpOZ6pwOT7ezYmJvpN9+98iJ2d3JUYohBDlI4+Z0lRCH5acnBwSEhJISEgAXElFQkIChw8fRtM0xo8fz8svv8y8efPYsmULt912G5GRkQwfPrxIOUuWLOHAgQPcddddJV7rs88+IyIiosRRSZUtJzeH6ZYlbD+wq1quJ8rG6SiotLLi4x/F0zOWHTuerLQyhRCivCRhKU0l1LCsX7+eDh060KGDa3joI488QocOHXj++ecBeOKJJ3jggQe455576NKlCzk5OSxYsACLxVKknOnTp9OjRw+aN29e7HWcTiczZ87k9ttvR6/XVzje8sjLzwPgr3+KH9EkakZwcH98vFuxbv217Nk7+YLWBtLrzcTG3E1W9mZstvRKjFIIIcpO5mEpRWX0YenTp8+Z+VyKoWkakyZNYtKkSectZ9asWefdr9PpSExMrFCMFXbqtk5mpXPixAlCQkKq9/qiWAaDF506zWb79ic4fPhTvDybEBl5XYXLCwy8DJ3OzKFDH9O4sdS0CCGqn9SwlOZ0nnEBM93WZU7nmb/c58yZg81mq8FoxNn0ek/atHkPP79OpBz7+YLKMptDaBh3P4cTp5OaurSSIhRCiLKThKU0Tlmt+XzUqe/PgB79SE1NZdGiRTUckTib3Z5NQUESFkuDCy4rJuYugoL6smnzXezYMeG8tYZCCFHZJGEphbJVvO2/Xjj10GoQFkn//v1Zu3Yte/fureGgxGlbtj6A3Z5JTPSdF1yWTmeibZsPadzoSZKSvyM5ZU4lRCiEEGUjCUspCnaeBEAVOGo4ktrJ3cdHp3HJJZfQqFEjfvzxRzIzM2s4MgGAUpjN4Xh5Na6U4jRNR2zsPYSHDWfXrokcOz6/UsoVQojSSMJSClO0DwCapXpG3VxsTicsOp0OnU7HNddcg8Fg4Pvvv8dul9lRa1p0zB3k5e0nN29fpZbbvPnLhAT3Y+vW+9m563mczsJKLV8IIf5NEpZS6LxdE7RpBvlWFed0p9vTM6l6eXlxww03kJSUxMKFC2syNAH4+XYEICN9TaWWq9d70KrVVJo2eY6kpO/ZvuNJ6dMihKhS8hQuTRXPdHuxc0/vcda3JyoqikGDBrF27Vr+/vvvGolLuBiNvoSGDmbP3smkpi2r1LI1TSM6+nZatXqTY8fmcejwx5VavhBCnE0SltJU8WrNF7vTE5JpuqK/Sl26dKFXr14sXLjQPcOvqBktW7xOQEB3tmy5n/z8I5VefljoYOJix7Jv3xukZ6yr9PKFEAJk4rhSufOVelbD4nQ62bd6OwV5BSinQiknTqVOvT/1cipOHDsOuDrd/lu/fv3Iy8vj559/xmKxlDhDr6haer2F2Jh7SEtbSk7uLjw8oir9GvHx48nIWMf2bY9wySW/YTT6Vvo1hBD1myQspTk9D0s9q4s6uvUgXy/8oUzHGpUerwCfc7ZrmsbQoUPJz8/n+++/Z/jw4bRp06ayQxWlcDrt7Nn7X7y9mhEUeGmVXEPT9LRq9T/WrB3Mzl3P0LrVO/UuyRdCVC1JWEpTT/uwFBZYARg18HrC4iPRdDp0Og1Np0M79VWn09Dp9Wh6HXpD8aOodDod1157LZ9//jlz5swhLCyM0NDQ6ryVei/xyEyys7fRufOcC1q5uTQWSyTNm/2XrdseJDmoN5ERFV8KQAgh/q2e1RtUQD3tw6Icrvv2DvTFNzQAn2A/vAJ98fT3xsPXC4u3ByZPCwazscRk5TSDwcAtt9xCaGgoX3/9NRkZGdVwBwIgP/8o+/e/RXTUaPx821X59cLChhARcT27d79Ifv7hKr+eEKL+kISlNPW1D8upzrQ6XeX8ipjNZkaNGoWmaXz++eekp8uqv9XhZPpKnE4r8fEPA7BixQqGDRtGZGQkmqYxd+7cIscrpXj++eeJiIjAw8OD/v37s2fPniLH7N69m6uvvprg4GB8fX3p1asXS5eeWV+oaZPneO+9NDp16ozZbKZ9+/ZVfZtCiHpAEpZSKKXqXe0KnFkj6N+jfy6En58fo0ePxul0Mm3atHMehKLy2QrTANDpXPMJ5ebm0q5dO95///1ij3/ttdd45513mDZtGmvWrMHLy4sBAwZQUFDgPmbo0KHY7XaWLFnChg0baNeuHUOHDiUlJQVwrRTt59ue/v2dXHvtoCq+QyFEfSEJS2mUqnf9V6DolPuVKSAggP/85z/ExsYya9YsVq1aJROOVSE/v06Acq+wPGjQIF5++WVGjBhxzrFKKaZOncqzzz7L1VdfTdu2bfniiy9ISkpy18SkpqayZ88ennrqKdq2bUuTJk2YMmUKeXl5bN261V3WJ5/8zI03tsDf/1h13KYQoh6QhKU0ivr5XTqdsFRBrubh4cFNN91Ejx49+OOPP5g3b16Rv+BF5Tl+4g/0em98fFqVeuyBAwdISUmhf//+7m1+fn507dqVVatWARAUFESzZs344osvyM3NxW6389FHHxEaGkqnTp3c5+l0RmJi7yEndxdOp63yb0wIUe/IKKHSOFW9678CZ9WwaFWTrel0Oq644gpCQ0P56aef2LlzJw8//DAmU9WNYqmP0tP/Jjz8Kjw8oks99nSTTlhYWJHtYWFh7n2aprF48WKGDx+Oj48POp2O0NBQFixYQEBAQJHzIiOuR69/isLC45V0N0KI+qw+1h2Ui1LU0z4sp2ewrdqbb9euHTfccAP5+fm8++67bNu2rUqvV9/YbOkYDf6VVp5SinHjxhEaGspff/3F2rVrGT58OMOGDSM5ObnIsXq9hcCAntjtWaSnr620GMrC6bRLU6MQdYwkLKWpp31YTi8RpKuGe2/ZsiX3338/kZGR/PDDD+zevbvKr1kfJKfMpbAwFS+vJmU6Pjw8HIBjx4r2Ozl27Jh735IlS/j111+ZPXs2PXv2pGPHjnzwwQd4eHjw+eefn1Omt3cLdDoPdu95EafTeoF3VJRSitzcfaQc+4XDiTM4evQbUtOWYbUeY+X/dWfJ0sZs2/4oR5O+xW7PrdRrCyGqnzQJlabe1rBUTafbkgQHB3PDDTfw/fff8+2339KrVy969uwpTUQVlJT8Azt3PktE+DWEhQ0r0zkNGzYkPDycP//80z0UOSsrizVr1nDfffcBkJeXB5w73F2n07lX7j6bpmlYLOHk5u4nIeFO2rT58IKn7VdKkZ6xmh07nqSg4Oip61twOs/tB5Wbu5eUlHns2/cGoaEDMZvDiQi/Br3eA6PR/4LiEEJUL0lYSlNPa1jUmSl+q+2aer2ea6+9lqVLl7Jy5Up27NjByJEjz+kbIc7vROqf7NjxJJGRN9Ks6YtF+mDl5OSwd+9e9+cDBw6QkJBAYGAgMTExjB8/npdffpkmTZrQsGFDnnvuOSIjIxk+fDgA3bt3JyAggNGjR/P888/j4eHBJ598woEDBxgyZIi73L1795KTk0NKSgpWq8JgeI6N/7xEbt71dOk8A4slslz3pJQiJ2c7x47P5/jx+eTnH8TfrwvNm72Mr28bjMYAV41L3l6yMjeRm7eHBpE34enZkPz8oxw6PI3MzH/Izz/M/v3/A8BiiUKnMxEePhy7LZOc3N34+rQmOvpOTKbAC/gJCCGqhKojMjMzFaAyMzMrt9ylh9XRSX9XapkXg02L1qoXXnhBZaacLLJ9+fLlaujQoSoiIkIB6qeffiqy3+l0queee06Fh4cri8Wi+vXrp3bv3u3ev3TpUoWr3uqc19q1a93HffzxxyoyMlIZjUbVoEED9dprr1Xp/dYliUe+Vov/jFc2W9Y5+0r6/o8ePVopdebnFxYWpsxms+rXr5/atWtXkTLWrVunrrzyShUYGKh8fHxUt27d1O+//17kmN69exd7ne9/6KL+WtlDZWVtL9O92GzZas+eV9X//d1XLf4zXi1b3kFt2/6kSk1dphwOW7m/N/n5SWrf/rfVkaOz1Z49U9TmLQ+oxX/Gq79W9lT/JIxRS5e1UUuXtVWZmZvKXbYQomLK+vyWGpbS1NcalhI6LJ6eeOzOO+/kmmuuOWf/6YnHPv/8c/df6AMGDGD79u1YLBZ69OhxTufM5557jj///JPOnTsDMH/+fMaOHcsbb7xBQUEBW7Zs4dVXX8VoNDJ+/PhKv9e6Jjd3L3q9Z7E/wz59+py3M6qmaUyaNIlJkyaVeEznzp35448/zhvDsmXLit1utR5n0+a72LDxRlq1fBOTKRidzoSmM6HXmdF0JpTThqYzkpW1iS1bxgIQEXE9zZpOJCCgu3sSvIqwWCKIb/hgkW0Ox6vodBY0TaOw8CSbNt/Flq0P0qP7kiobJSeEKD9JWErjpF72YSlpSYJBgwYxaFDxs5eqf008BvDFF18QFhbG3LlzuemmmzCZTO4OnAA2m42ff/6ZBx54wH2tL7/8kuHDh/PQQw9ht9tZvHgxJ0+eZOLEiVx99dU0bNiwCm64bsjJ2cXRo1/RKP7RC+4rUhXM5lA6dviGjf+MYvOW/5TpnFatphJexn44FaHXe7jfm0yBNG70JBv/uZmMjLUEBHSrsusKIcpHEpbS1PcalnLcemkTj910003nnDNv3jzS0tK444473NusViuenp6Aa+HEgQMHsmvXLubPn8+yZcskYSmB02ln567n8fCIIzr6jtJPqCEGgxedO31HXv4hUE6czkKcqhCnsxDlLEQpJwUFSfj6tcPXp3W1x+fv3wUfn9Zs3/EUHdrPwNNTft+EqA2kvrMU9TRfOTPTbTnWEirLxGP/Nn36dAYMGEBUVJR724ABA/jxxx/5888/cTqd7N69m2nTpgGwatUq1qxZU+yIlPpMKQfbdzxOVlYCzZtNQqer3aOrdDoT3l5N8PZuhq9vG/z9OhEY0J2goN4EB/clKmpUjSQr4JossU3r99HpjKxbP4Lc3L2lnySEqHKSsJSmnmYsp3s5VOU8LEeOHOGPP/5gzJgxRbbffffd3H///QwdOhSTyUS3bt3ctTPNmzdn/vz5fPnll2RkZFRZbBcTpRQ7dkzg+PHfaNVqqjRjVAIPjyi6dP4RTTORnDynpsMRQiAJS+kUUE1zkdQm7n6Z5bj1skw8drYZM2YQFBTEVVddVWS7pmm8+uqr5OTkcOjQIVJSUrjkkksAuPXWW7n11ltJS0vjww8/5J9//qn3M5qmpS0jOWUOLVq8RliorI5cWTTNiNOZL/O1CFFLSMJSGqXqZ6fbU3PdlmeUxNkTj512euKx7t27FzlWKcWMGTO47bbbMBqLH/Wh1+tp0KABJpOJb775hu7duxMSEkKjRo247777aN68OT///DPffPMN2dnZFbjHi59STpKT52AyhRIRPrymw6lTcnJ24HDk4e/ftaZDEUIgnW5L5WoRqn8ZS0k1LBc68dhpS5Ys4cCBA9x1113nXDs1NZUffviBPn36UFBQwIwZM/j+++9Zvny5+xgPDw9GjBhB8+bN+fXXX/nggw8YOnQorVqVvipxXaGUYtfuiRw/sYBWLf9X0+HUOR4eMQDk5R/Ez699zQYjhJCEpVROhbPQQd6WE6hCJ8rmRNkcp746walcTRJOznqvQJ2a3l6BptdAp7mmuddwNTHpNFcipAM0zdVNxr0d3JnCv3Ml7V9vNM6cq7nKd19HO6u8059PX6u4a5/arhl0OLILXcX/K1lbv349ffv2dX9+5JFHABg9ejQzZ87kiSeeIDc3l3vuuYeMjAx69erFggULsFgsRcqZPn06PXr0oHnz5sV+2z///HMee+wxlFJ0796dZcuWuZuFztaiRQtiYmL49ddf+f7779m5cyeDBg1yjzKqq5RS7Nn7CkePfk2L5pMJD7+q9JNEuZhMQXh7Nyf95N9SeyVELaCpOtIBICsrCz8/PzIzM/H1rbz5J7KWJpL1x8EzGzTQjHo0kw7NoDsnEXEnIaffa6cSF4cCpVBOXNUXTuWqxXCWsB3O9Hw9/ebfPynl+o/7XKXOzCl6gfbpUlhq2saEx5/C7GUp/YQappRiy5Yt/P777xiNRq666iqaNCnbon8XG6UU+/a/waFD02jadCLRUbfWdEh11o4dE8jO2cElXebWdChC1FllfX5LDUspfPpE4dUpDM2oQzPqQK/V+iYi5U5citb0FEmIzjrmTMJzOrlycmLXdliyzXXPFwFN02jbti2xsbHMmzePr7/+mk6dOnHllVdiNptrOrxKo5Ri377XOHT4Y5o0fkaSlSpm8Yji+In5KKVq/f/3QtR1krCUQtM09L61e06Lfztds3O62agi/8zqUkxnyrqI+Pn5ccstt7B+/XoWLlzIvn37GDp0KI0bN67p0C6YzZbF9h2Pk5q6mCaNnyEm5s6aDqnOs9ky0Ok8Lrr/D4SoiyRhEXWOpml06dKFRo0a8fPPP/PVV1/Rtm1bBg0ahIeHR+kF1DJKOTl69BsOHHwPp7OAtm0+IiSkf+kniguilCI1dTHBwZfXdChCCCRhESU43bXpYv7LMjAwkNtvv51NmzYxf/589u/fz+DBg2nevDm6cszgW5MKC0+ybdvDnEz/P8LDrya+4SN4eDSo6bDqhZzcXeTnH6Zpk+dqOhQhBJKwiFJczAkLuOJv37498fHx/Pbbb3z33Xd4enrSr18/2rdvj16vr+kQS1RQkMQ/Cbdjs6XTof3nBAb2rOmQ6pXExBmYzeEEBvaq6VCEEEjCIkpQRwaPufn6+nLTTTdx+PBh1q5dyy+//MIvv/yCOeUwnTt1pPt1N+MdEFjTYQKuRQyPJn3D/v1vYTB407nTd7IAXzU7efJvkpPn0KTJM7V+XSYh6ouLo15c1JiLvYblbJqmERsby/XXX09kYAAA1vAYvv91Pl1btyTAxxtN0/jg1VfIzUgvcl5xr9dff919TFxc3Dn7p0yZUq74HI48kpN/ZN36q9m9+0VCQwbQpfNPkqxUI6UUu3e/RMKmOwkI6E501G01HZIQ4hSpYRHFqgt9WM7n8n6Xs+i33zienYPeP5CeffoS5mXh5U9msu6XH8nf+DcRTZvT5vIrObBvLxZPL/e58+fPZ8yYMVx77bVFypw0aRJ33323+7OPj0+pcdjtOaRnrCHx8GekZ6wFnAQE9KBL5x/x9W1bafcryiY5eQ6JR2YS33A8MTF3oWm1t8lQiPpGEhZRrLqesDRu1YbGrdrw0nPP0qVjB+58yDVj78ufzOTK/zxEh4YxbFmykIUfvQtK4eUfQLPul9KqT3/mfP89ffr0IT4+vkiZPj4+xS7yeDan04ZSTjIz15Oc8iPHjv2KUnYslmhiYu4kqsEteHhEV9l9i5IppUhM/IyQ4Cto2PCBmg5HCPEvkrCIemvdunU49AaO7dhC2tFEghq4EgUPbx+a9+xN8569yTmZxvrf5rLh15/YOH8ey3/6nvkL/mRktw447Db0hjMLN06ZMoWXXnqJmJgYbr75Zu67527SjxzmxOGDFOTkkLR3IwFdf3Ifr9OZiI4aTYMGo/D0jK32+xdFFdrSyMndRYOoW2o6FCFEMSRhEcW6WGf2tNlsJCcnA67Vng0GA3q9/pzX7t27+e2334jw8yF/XxafPzqOhh07A3Bk5zZgOADegUH0uXUMvW66jdz0NN544008Fq6kdWQoU0eNoO/t96A3GBnRvy9N4+LQ2QpYt2EjLzz7LL9++iFXtW+J3mjEw9sHLMkEnIrzki6/4O3dTJocahGTMQhPz4ZkZ20BGTkuRK0jCYso1sWUsOTl5bF792527tzJvn37sNlsZTovPj6eW2+9FYf9QTYv+p2969cAcOCf9eccazAa8QsN5/t5vzD6jjto3jCCfevXsHTmxwBEAY59eXiFhDK8/+WERsfy+ief8dW834iIb4zBaGT7uhkkZ79MiOd4fHxaVtr9izOs1uMkJX1HRMQ1WCyR5TpX0zSCAnuTmrqkiqITQlwISVhEsWoiYXE6nWRnZ5OZmUlubi55eXlERkYSERFxznGJiYns3buXxMREDh06hFKKqKgoevfuTaNGjdDr9TgcjiIvu93ufm+xWGjYsCGapmEwGuk4+Go6Dr6aG1+YXOJ9//XXX+zatYtvv/2Wdu3aoZQiJz2NnJNp+AaH4uUf4D624bZtTJ72CXnoMBhdzUan+wU1iOtbbPmiYpzOQmz2LLKzNrNps6vT8/4Db9Gj+4pyT7Kn13uilL0qwhRCXCBJWESxqjNhUUqxa9cuFixYQEZGxjn7o6Oj6dmzJ2FhYWzYsIEtW7aQmZmJl5cXERERDBkyhGbNmpVpVE5ZaCXMgjt9+nQ6depEu3btXMdpGj6BwfgEBp9zbEJCAjqdjtDQ0DP36XSeOk9mE6gshYVp/LXykmL3/b3qMsLDh9OyxRtFfpeVUtjt2djtWSjlwGDwwm7PxmbPIjdvL0ZT7ZiPRwhRlCQsoljVlbAcPnyYJUuWcPDgQRo1asTgwYPx8/PDx8cHk8nE7t27WbNmDbNnzwZc/VLat29PmzZtiImJqZQp9k+eOM67D4+jIC8XgBOZ2SQkJBAYGEhMTAzgWv78+++/58033zzn/FWrVrFmzRr69u2Lj48Pq1at4uGHH+aWW24hIOBMrYvi1Miri2RZgNouJ2cXa9YOLnaf0RiI3Z5JSspccnJ2o9MZycrahE5nQSkbSjlKLDcsdGhVhSyEuACSsIhilXem28LCQhYvXszBgwcxGo3ExcURFxdHTEwMZrO5SLmpqakcOnSIHTt2sG/fPsLCwhg5ciRNmzY9J0lq2bIlLVq04MCBA+zZs4eOHTsSEhJSKfd42v/9tYKJX//g/vz57wv5/PeFjB49mpkzZwIwe/ZslFKMHDnynPPNZjNffTGDZ595HJvdSXioB8MGxjLyWh3rlj6Pp3cUPv4NKcg/BoCmk//tLoRSiqNJ37Bv35t4esbj69uOkJArCAm+AlDujsxW67FTC0YW4nRaycrahNNZQLOmk9i9Z9I5TT8+Pq1o1fJ/WCxRNXBXQojSaKqOzMGelZWFn58fmZmZ+Pr61nQ4F71vvvmGXbt2MXHiRPc2pRTHjh3jxIkTZGRkkJubi7+/PwAbN24kPT2ddu3aUVBQwMGDB8nJyUHTNDw9PbFYLFgsFtLT08nLy0PTNCIjI+nevTstW7as0cUIv3zyIY4f3AdAvzFjiWjclLD4xuUqY/3Sl8lUMyjMCEZDh6IAzZiPwcPGv1uAunf5G0+fsMoKv1ay27PR673PaYqpjFq7gwc/ZN/+N4gIv5b4+PFl7lz755JGAPS7fB8ORx4pKfMIDOxJesYadux4EoCePf4qd2ddIcSFKevzW/7UE8VKT3dNTb9hwwby8/NJTU3l4MGD7j4mFosFLy8v9+ewsDDuvvtud5+N0zUphw8fJicnh4KCAgoKCoiPjyc2Npbo6OgiNS816XSyAvDn9A+IaNKMm18+t+nnvHQ6cEDfQQuxePi5N9us+WSk7iXz5H5ysg6i15vrZLLidNrZveclTqatIL/gsHt782b/JTR0EDt2TuDEiYVomg693ouI8GsIDr4chyOX1NSl2O3ZGIx+xESPwcsrvsTrZGZtYv+Bt4iLvY9GjR4rV4wBAd1JT19FZmYCfn7tadDgJgAslgbuhOXgoWk0bzapAt8BIURVkxoWUawdO3bw3XffoZTCYrHg7+9PdHQ0zZs3p0GDBlgsFsA1Yuf02jkXqzdvLNpnYfzXPxWZEO585n87EL3fPjSdQmdQ9Oy2HotnQOkn1hFOp50jR7/k4MEPsNlO4u/XBV+/9hw+/In7GKMxCKUcxMXdh17vSUH+EY4mzcZuzwTAy6sJZnM4ubl7KCxMpUXzV4iIuPaca+XlHSBh050YDH507vQ9Ol3Zfkan5ebuY/WaK/HyakK3rgvc2wsKkvm/v3sR4N+NjMx1XHLJb3h7Nangd0QIUV7VUsMyZcoUJkyYwEMPPcTUqVMB+Pjjj5k1axYbN24kOzub9PR0d7NBSSZOnMiLL75YZFuzZs3YuXPnhYQnLkCLFi14/vnnS01EarIpp7J0HHw1B/5Zj72wkLh2HdzJyomkLeSkHyU8tise3sUnIcqQhCoIxMvcDYslsl4lK1lZW9i56xmys7cTGXkDgQE9CA7uh17vQZPGT5GVtYXEIzMxGFw1J2cPMW7U6FHy8w+jlMLT0zW83OGwsnPXM+zc9RwBAT2wWCJwOPIAPampi9mx82nM5hBat3q73MkKgOnU6J/c3D0UFCS5m36s1hQAGjd+ks1bxnLo0DRatSxnDZsQospVOGFZt24dH330EW3bFl2gLS8vj4EDBzJw4EAmTJhQ5vJatWrF4sWLzwRmkNaqmnYx15qUR9/Rd9N39N18+dRD6PSuDptrljxJDq6OuHt3teSKa34p/mSdwmxsTM9Bb1dXuJXC6bSjlAO9vmLNckeOzmLXrhfw9m5G585z8PNtd84xvr5tSnzwa5r+nFWo9XozzZq+QFraclavGYjB4O1OJsA1eqd58/9iMHiXO978/EQ2bDzTYXr1moF0vWQ+Hh4NyMrajKaZ8PJqTEzMGPbunUx8w0fKPYeLEKJqVSgryMnJYdSoUXzyySe8/PLLRfaNHz8egGXLlpUvEIOh1IXjhKhSCpL27OLw1k2kZ6zB6A/WLBOa/hAJ/zeV9j3Hn3OKpik0Lp5aJpstg/37p3Ls+G/Y7Zl4eTXDz689fn6dCAnuh8FQ+lw2ubn72LXreaIa3EKTJs9UqLajJAaDD21av8vRpG/xsETh6RlHVtYWTOYQ4mLHViiJLihIYuM/o9DpTPTs8RfHT/zBnj0vn2qSaoC18DigKCxMJ8C/K0o5OHZsHnFx91XafQkhLlyFEpZx48YxZMgQ+vfvf07CUlF79uwhMjISi8VC9+7dmTx5snsOjOJYrVasVqv7c1ZWVqXEIeqviKbN2bZ0EevmzcGrucKWEYW3pSlW/TLSrO+y6W8dzTqMLtKpFk1BLU9YlFIcP7GAjPQ1nExfidV6ggYNRuLhEUNW1mbS09dy9OgsPDxiad9u+jk1H/+WlPw9BoMfTZpMqNRk5bSAgG4EBHRzfy6uP0tZ2GxZHDj4DseO/YpOZ6Fjh68wm8M5fHg6oaGD3csjxMbcQ2LiTA4d/hiLORzQiIi8vjJuRQhRicqdsMyePZuNGzeybt26Sguia9euzJw5k2bNmpGcnMyLL77IpZdeytatW0ucvXTy5Mnn9HsR4kL0H3Mf+VmZWE9NIAdw2eBPWLP4WXL4htSCt0n+4zO8zL3QaQZ0OhMmnwLIq70Ji8ORx44dEzh2/Fc8PRvh5dWU1q3fw8e7ueuABjcDsG/fGxw89CGrVvenTZsPCA0ZUGx5TqedlJS5hIcPQ6erHaO8iqOUk63bHiQz8x/Cw4YRFzcWiyWSnJxdWK3JNIh81X2s0ehHo0aPsWfPy+45XIwG/xqKXAhRknIlLImJiTz00EMsWrTIPUqkMgwaNMj9vm3btnTt2pXY2Fi+++47xowZU+w5EyZM4JFHHnF/zsrKIjo6utJiEvWT3Z6LR4sfMPoXYstw/T517f8yeTkPsXzxAHSmXPLUIjTNiYZCB+cdhluTnE4rCZvuIjt7C61bv0tYaPGzwgJ4eJypzdyyZSwN4x4kLm7sOTUoJ04soLDwBBER11VZ3JXh6NFvOHnyL9q3m0lQ0KXu7ZmZG9E0Pb6+7YscHxN9B3q9Jzt3Pg1Abu4ufHxaVWfIQohSlCth2bBhA8ePH6djx47ubQ6HgxUrVvDee+9htVrRn+q0eCH8/f1p2rQpe/fuLfEYs9lca+bxEHVHRvo6YvwLAfCynHlgeXqHMGj4xpoKq9yUUuzd9zqZmRvp2OEr/P07n/d4i6VoB9MDB9/BZk+nWdOJRbYfTpyBj3crfLxr98M85djPhIRcWSRZAVfC4u3dHIPB65xzGkTeSFraCk6cWEDayZWSsAhRy5SrLrtfv35s2bKFhIQE96tz586MGjWKhISESklWwNWpd9++fees0itEVfOLdfWLat/yFy4d/H4NR1N+Sjk5fHg6q9dcQWLiDBo3erzUZAXAbD63w/uRI1+SmXkmScvPTyQrK4GwsKG1egSZUorc3N34+pw7cikjcyN+fh2LOcslOKg3ACdP/lVl8QkhKqZcCYuPjw+tW7cu8vLy8iIoKIjWrVsDkJKSQkJCgrt25HSCc/LkSXc5/fr147333nN/fuyxx1i+fDkHDx7k77//ZsSIEej1+mLXbRGiKjXs0AmAgNDmNRxJ+Vmtx9m+4wn27J2Mr287OnT4ipiY4ptU/62k0UFbtj5AQUEyAGmnHuIBgT0qJ+AqYrOdxG7PxvKvYclOp42CgkS8vJqWeK6HRywA6emryrWelnI4yVxwgLRZO8q9DpcQomwqfbKTadOmFekMe9lllwEwY8YMbr/9dgD27dtHamqq+5gjR44wcuRI0tLSCAkJoVevXqxevbrSF7kTojQ+QWHk2ytnFejq4HTaSEmZy9Gk2WRlbULTjLRq+T/Cw68qVzlGY6D7vU7ngdOZT0zM3Rw79iubN99Lp07fcfLk/wHgYSl59F5tYDD4YTQGkp29lfCwYQAUFqaxe/ckQMPPt0OJ51qtx856n4LFUnotr7I7Sf1sK9b9rpl7C3tmY46V2baFqGwXnLD8e76ViRMnFlkwrzgHDx4s8nn27NkXGoYQlULT9DiVrabDOK/CwpNkZ28hK2szSclzKChIJDjoclq2eJXg4H4Yjf7lLlOnM6BpRpSyYbE0IC9vL4WFJ2jX7lPWr7+GLVvuIztnJ6GhgzEaa/fDWKczEBzUh/T01SilOJG6kN27XsRmz6Bli9fw8WlR4rn5+WfWQcrLP1imhCV7+RGsB7MIvrsN6d/tJm/jMUlYhKgCMp2sEGdxPbQdF1SGUk6s1mMoZcNsDkenM53arsjPP0yhLRXltOHv37VIXxCr9TjpGWuw27Lw9IzDbs/hZPpKfH3aEhzcj8ysfzh0aJq7X4nB4EdgYC/atp12ZpjyBfDyakJOznYs5nDy8vZy/Ph8WrV8k6ZNnmPnrmcBaNzoyQu+TnXw8W1DcsqPrPy/bhQWphIU1JfmzV4qNQHJLziCt3cLcnJ2YC1IOu+xyu4ke+VRshYdwqtbBJZG/nh2DCVnVTL+QxuhGS+OWjohLhaSsAhxFp1mxGZLZ/OWcShnIWZLOJ4ecXh4xODpGX9q3RvXg0gpRUFBEhmZ68jMWE9G5noKCpJPrX/jPF0iHpYo9HoPbPbMIlPN+/q2IzR0EJpmIDtrC8eO/4ZSdlxdy1znWywNOHp01lnntKdlyzfx822Ph0dspXZ+NZtDyMnBvcaO02nFbs8mMvImsrK3YrUeK1ONQ20QGXEDdns2DnsuQUG98fe/pEzfK7s9C73eC00zUWhLP++xyZPX4sy1YQj1xKdPFACencLIXppI7oYUvLtFVsq9CCFcJGER4iyhoYPIy9uP1XoMnc5EZuZGkpN/wunMB8BoDMDPrxM6zUhm1j/uBMTTszH+/p2JiIhDr/fCYo5A0xkpyE8kL/8QTmchOp2RAP9umC0R2ArTOHDwfQ4ceAelnHh4RNO40ROEh4/AaPQjL+8Qer0FiyWSvLwDZGYm4OPTCi+vJlU2QsdkOrfPWHb2dgICutKi+X+r5JpVRa+30DBuXLnPM5vDOHHiD3Q6E0GBl573WO/uEWQtPkzYA+3RjKcmnAv2wLNTGFkLD+HZNgSdZ+XPBCxEfSUJixBn8fSMpWXL14psU0pRWJhKbu5uMjLWkZG5AbtyEBY2FH+/zvj5dXKvBFwegYE9S9x39mR0np4NS50uvzKYTyUshbY0QkMHc/z47+Tk7iIgoGuVX7u2iI66jdyc3cTHP4y3d7PzHmuMco2scuTZMfidmdLBb2Ac+VtTyVx0iICrG1dpvELUJ5KwCFEKTdMwm0Mwm0POm2Rc7EzmUAAyMtbTseMsPCzRhARfUcNRVS9Pz4Z07Ph1mY41BLpm+7afyMPgd2YSS72PCd9+MWTOP4DXJRGYIs6dpE4IUX7SK0wIAUBAQHcA7PZMfLyb07jxExdNn5WaYAj2QO9nJnvFUZTdWWSfd49IDCEeZPy0B+WUeVmEqAySsAghAPD2agK4RkqJ0mk6jYBrGmPdm0HK6+tI+3oHOWuSUUqhGXQEjGhC4eFsctck13SoQtQJkrAIIYpQp+ahcToc7NuwBqfjwoZ512WWZoGEje+IpUUQjhwbGT/t5fj7CdjT8jE39MPrknAyFxzEkWmt6VCFuOhJwiKEcDOp1ng4hgJwaEsCc197ic2LF9RwVLWbMdSTgOGNCb23LcF3tsZxsoCT3+5CORR+gxqiGXVkzD9Q02EKcdGThEUI4bb2YwerPt0HQGica6TSxvnzajKki4qlaQBBo1tReDib7KWH0XkY8BvYkPyEE+RvT6vp8IS4qEnCIoQ4h1IKL/8AANKTj5Z4XNLunWxZurC6wrooGMNdo4KyFh9GORWenUKxNA8k/cc9OHJr97IPQtRmkrAIIc5RmJ9f5LPDXvyDdv2vP7Jw2jvs27CmOsKqVSZPnkyXLl3w8fEhNDSU4cOHs2vXLjSjDnMTfwAu69QDnU5HyB2tafBcdwzeJv7zn/+4y0hLS2PgwIFERkZiNpuJjo7m/vvvJysry31McnIyN998M02bNkWn0zF+/PhqvlMhagdJWIQQboGRrinm8zLTWTn7S/f2bcuXFHt8t2tuAmDuay9hsxZUfYC1yPLlyxk3bhyrV69m0aJF2Gw2rrzySvLy8wgZ0wavbhHY063cdccYkpOT2bdoCxvG/cTE255wl6HT6bj66quZN28eu3fvZubMmSxevLhIUmO1WgkJCeHZZ5+lXbt2NXGrQtQKMnGcEMItKCqGk0lHWP/LT2z+cwG+IWFknTjGoo/fpVGnS9zNRKc57Xb3+7U//0DPG26p7pBrzIIFRTsjz5w5k9DQUDZs2MBll12Gb/8YUApDhpPw8HBUWBgnU3RYFx/D0SYKvY+JgIAA7rvvPncZsbGxjB07ltdff929LS4ujrfffhuAzz77rHpuTohaSGpYhBBuQdGxABTkZAMw/InnuPTm2wGY+/pLOB0OlFKkJh4iNyOdxdM/wCsgkDb9BrBu3hwyjqWUVHSdl5mZCUBgoGuZBr23Cb2Pie/++Ing4GDatGnDa//MJN9u5eT3u4udUC4pKYkff/yR3r17V2vsQlwMJGERQrgFn0pYAiIbAHD8wD4uufo6+o6+m5R9e3jr5qv5303D+PyxcUy791YyjiVz7YQX6Xvb3Xj6+rPsi09qMvwLUlKflLMVFBQwbtw4goKC8Pb25tprr+XYsWM4nU7Gjx9Pz549ad26tfv4m667kbeHPMuCGT8zYcIEvv52Fo+sfhPrnnSylx9xHzdy5Eg8PT1p0KABvr6+fPrpp9V230JcLCRhEUK4efn7A3Dy6BE8/fzJOnEcgI6Dr+aWV94ivmMXAiIiAWh5aV9GTnqDkNiGGC0W+tw2hn3r17B/47qaCv+ClNQnJTc3133Mww8/zC+//ML333/P8uXLSUpK4pprrmHcuHFs3bqV2bNnFylz7NMPcXnrHjQqDGXUqFF88cUXzFv0K6lNnWQtPIj1sKtz7VtvvcXGjRv5+eef2bdvH4888ki13rsQFwNNKVUnFrrIysrCz8+PzMxMfH19azocIS5K6SlJfPbQPXj5B5CbkU5M67Zc/9wrZTpXKcWcV54nPTmJLsOuITczA7OnJ9lpqQQ1iKZt/4FVHH3lOnHiBKGhoSxfvpzLLruMzMxMQkJCmDVrFtdddx0AO3fupEWLFoSGhrJ69WoaNjx3Ve3slUfJ/G0/4Y92xurhxNvbm/m/zafDgXCcOYWEjmuP3tvkPn7lypVceumlJCUlERFRdC2nPn360L59e6ZOnVql9y5EdSrr81s63Qoh3PxDwwHIzUgH4PDWzWU+V9M0Lr/jXmY8/B/+/OxDPHx8cdht7iHSgQ2iiGrRupRSao9/90nZsGEDNpuN/v37A64E7b333kOv1zNmzJhikxUA767hZP5+gILd6WxSrhlvI6MiCerelOPvJ3Dyu90E39EKTdMAcDpdCylarTKdvxBnk4RFCOGm6XQ0aN6Sozu3A+AfVr7VmgMjoxj13/+RmniI1n2vAFxrEn39zCOs+uEbrnv2ZfeDuTYrrk/Kxp0H0BmMzFx/nPH9/Rk3bhyzZs2icePGZGZmkpLi6nDs5+eHh4cH+/btY9asWQwePBjlmcWSz7/jxcXvctlll9G2bVsA1oQeYv8PCfR0Xk54/yZs27aNxx9/nJ49exIXF+eOJyEhAYCcnBxOnDhBQkICJpOJli1bVuv3RYiaJE1CQogi8rOz+OCum92fH/321wsuc++61fz8xsuExTcmqkUrmnbrRWTTFhdcbmWaPHkyP/74Izt37sRut6NpGl9+/xMN21zC8Swrtz79Jqm/vFFqOa1btyYtLY20NNdU/JqmoRyKSJ8QrrpyKFfeOoyhQ4eec57ZZCYmNoZrrrmGp556Cv9T/YlOl/FvsbGxHDx4sML3K0RtUdbnt3S6FUIU4eHjy7XPvOT+bM3LpbAg/zxnlK5xl25c/diz+IaE8s+CX/n+pWfJOVn+tXVKG8kzefJkfH190TStyOs///kPubl7OXDgPbp373zO/tatW/Pnn38ybtw4rrjiCux2OwUFBVw3dCCdYgMZ3Lkx+Yc2ARDReQBtHp/NsxMn0bhxYwBCQkL4/PPPOXnyJGPHjnVPBPf7778TFxfHtddfy6pn5jLxxkfx8nJN3b9r1y6Sk5NJOprE1qnL2PPUn2z7vwSmTJlSJFkBV/PTv1+SrIj6RhIWIcQ54tp2wDsoGID37riRd0dfz5KZH11QmY27dOOqR55m7KezMJjN/P3DrHKXUdpInuXLlxMZGcm1117L4sWL6devHw0aNODBBwezes0A9h94C5stnZ49ezJ//nzWrl3Ld999h9VqJTQ0lPXr17Nq1SruuHMMI24fC0CDPqMwmy3kb3XN9tvYV3F00wpef+1Vxo51HfPAAw8wbtw4Vq5cyX333Ufnzp2JjY2lX79+jB07lr/++gvNoAPdmZqS0NBQwsPDiYiMoMU9PTH6mkn7fLusNyRECaQPixCiWDlpqUU+63T6SinX7OlFtxE3sPzLz2jbbyDhjZqU+dzSZpddsGABffr0ISoqin79+tG2bVtCQ0NZs+ZTmjQNx2pNwWTyoHPnzgwc6Bq11KVLF5KTk3n66adxKA2/q59hvjEKe+4xABp16csTIy7hqaeeAmDl0sUoFuPt7c0bb7zBJZdcwnPPPUdGRgavvvoqw4YNc8d39kRwTqsDnfnM97B9+/ZYrVZat27NxIkTuWR0R46/+w8nv9lJ8J2t0XS1v6+PENVJaliEEMUye3qhaTqGjn+KcdNn0+e2uyqt7Lb9B6KUk0Ufv3dB5fx7JM9pX3/9NcHBwfTo0QMAa+EOLGZXB2KDwdu9v3Xr1txzz0hmTptEbm4uBXk5HPtmAkfev5WUrx8DIDz/AF988QVKKUaMGEH7Hn0BRU5ONidPniQoKAgADw8P1q5di81mK3YiOGeeDZ2HkYiICKZNm8acOXOYM2cO0dHR9OnThy2HdxB4c3Os+zLIWnjwgr4vQtRF0ulWCHGObcv/ZMEHbzHiqReI79ClSq7xzXOPo5xObv7vmxU63+l0ctVVV5GRkcHKlSvd2z/++GNiY2MJDw/n9ttvZ/v2bVxyiZGpU4eRX5DItq23ERcXxwMPPMCePXsA0IDeXl48HhrKj11vY3nyZvb93+8o+7lDi++9915+351N0rp5dLr2CtZ+/hNmXz+sWa7k6fbbb3fV1jgc7N69m9tuu82dWJ2tZcuWbNu2DYDevXsTExPDl19+SdayRLIWHMT/6kZ4d4+s0PdGiIuJdLoVQlRYwsLfCIqKqbJkBaD9wKEk793Fkhkf4ThrEcWyKml22XvuuYcBAwYwbdo00tPTef31m1m5Mo9Dh04Q4N+Ve++9lyuu6EeDBpHcdXc4w6/0RQHbCgq4KzGRrCXTKNi3jpGTPsUYEodndAtCQ8MwmUx88MEHvPbaaxgubYkx2M7az38CwJqVif7UEPClK1bwwgsvEBLfmMcnv3pOsnJzGzOBHhrXBe8n5anWDLi8Lxs2bODrr78mOjqap394FWcHHzLm7SN/u6tjstVq5ZlnniE2Nhaz2UxcXJwshCjqHUlYhBBuSikOJmzg2P69tOrTv0qv1bzHZfS+dQz/LPiFn19/ifJU9t5///38+uuvLF26lKioqPPub9/e9dDfvWcH/v6XsGXrAyxd1ozXXg/kppu8ee66awA44XCQbLezKC2VBZ99xgfjbyQ2IhR9aBOeeesTCgsLeeONN/hm598ERK/H4G0gaLCrOeiBDz9F8/AETSO1/zDmLVnGyE37SM0+yZCmrq6Ca+/yJPlRb67s1JP0Ahh13cMYVCZDfY7SqmVLrrzySmbOnMnixYt5au5reLQM4uQ3OylMzOaGG27gzz//ZPr06ezatYtvvvmGZs2aXeiPQIiLi6ojMjMzFaAyMzNrOhQhLkqHt25Sb9wwRL1xwxD13aSnlc1qrXBZr7zyiurcubPy9vZWISEh6uqrr1Y7d+4sckzv3r0VUOR17733uvenpqaqAQMGqIiICGUymVRUVJQaO3asuvvuu1VkZKTavXu3mjNnjurfv78KDg5WPj4+qmvXrmrYsGHu/YWF6Wrq25EKUB9/3EAt/jNebfxntFr8Z7xa/Ge82r//XbX8z0VFYnilSROV8OijKjk5WYU1bqN0Hr7Ky9vbtV+Pavh0Q9X09aaq3aNXKmOIUTXt3EYppVSXbt0UoAIiGyiv7pepjj8uUjHRISrAQ1Pd2zVT6gVfpV7wVS1btlTt2rVTe/bsURu/+EA92NWkdJqmFi9erJRS6u2331ZRUVHKWWhXx97/R3112/+Un6+fSktLq/DPQ4jarKzPb0lYhKjnHA672vF/y93JyuwXnlROh+OCyhwwYICaMWOG2rp1q0pISFCDBw9WMTExKicnx31M79691d13362SkpLU9OeeVI8++qh67+2pymq1qldeeUV16NBBmc1mFRAQoK644go1Y8YM5e/vr4xGo1q2bJnq3r37OQlPQECAAtT99w9S8+dPVe+886gKDdWrVq0DVHCwXgGqd29fdcutAeq7715Tr732mrJYLEr7Vzlnv8yx7ZXe2+L6rKH0BoMyGo3KO8hfBVwWoD766UsVExPjPt7X11f5+voqs8mozAZNWYw6FRgQoFqG+aj7RgxWOp1OhYWFKYvFogL9/VWfOL1a8MqTSimljh49qnr37q1GjRqllFLKnm1Vo7tfqy5t0kU9/shjKjIyUjVp0kQ9+uijKi8v74J+RkLUFmV9fkunWyHqIaUUSbt3krJ3N/vWryZx+xb3vke+mYemq9zW4rMXErz00kv56YuZPPPyK7Rs0YyH7vsPWZlZrN+5G3DNT/LDDz9w22230aVLF+x2O08//TRbt27l8OHDxZY/depUrr9+OA0axBW7v3ETXwIDbKxdm09srJEjR5w4HA4AzGYzAZ4mUtOzuaZXW+566DnuGDmSZIcDp1KgaXj4BOA72MiV3a7ky/FfsmDBAkY9cDcnDx3Bx+JD9+7dOXnyJNnZ2eh0Onr37s2UyJ+ZveYkuW0G0n/kJDZv3szYsWMpKCggOzsbk8lEwXdvYd42iZFb+zJv/gLy8/MZNmwY3333HRaLhdTUY1w/4gZWrV7Npc278vJHr5GW4Zqcrm/fvsyYMaNSf05C1ISyPr8lYRGininIzeHbiU+Revgg4Bq+3KhzVyKbNqdt/0FVstbP3r17adKkCVu2bCE8JJj3PpzGzJkzOXHiBEopvL29adq0KS8//xxbd+8hMzOTIUOG0L59e+BMwtOuXTtat27NV199VWTl4oK8XDZt+C85th+57dZUnnzyWfpevp/jx39j3rws1q+L4N57uzB69GccPLiC2NhL3bGNCghgSU4OIR5Gegy5gv/2G8bxN97EZ+BAoqa+5T7uw4QPmb5hOhvu2sB/Z/6XdVF69h75ige6vc2Cx55n1epNfPTuk2Q7ArjllvtJesSbI9e8T5eetwGuJDE6OpqjR4+yd+9eGjVqhPXN69DlH+HEtR+TtiOB3ZvW89z02VwaH8w7Qxui5SQx8KtU/j56go0P/ExYhxgCRzbnp7k/cd1115Gbm4uHh0el/7yEqE6yWrMQolh71v5NauIhrp3wIn5h4Xj6+WP29Kqy6/17IcGNq/4G4NphQ+jasxchgYFs3rKVKW+8wTvTPmL27Nn89ttvzJ07l3379jF79mx++eUXAPz9/fn000/dZX/99dd88fmXWDRfWsd2p+PAS8jP/5WbbrqZoCAftm3byldfrmDV30vZu2cv8Bl6nQ/Z2duxO/J4/LHJLLbmMjM6hldjorGENSRt+mdYWrYkYuILRe5jWKNhvP7D6wDMSJyBl8E1Kuj7l99nx4rV/H27BzE73+T/DhUCYHVAUOSZ1amXL1/O0aNHAdwJi/KJxpi9iMhvLyUSaKNByBVGes/cwYReYYRZsoj0sRLmGYRqayF/ayqZv+2nefPmKKU4cuQITZqUfeI9IS5mkrAIUU8c3rqZfetXs235n8S160hc+07Vct3Tw49Pz5WyfccOAO68cwytOnQEoO+VA2jToQP9+vUjMTGRESNG0KhRI37//XcaNWpE06ZNKSgo4MSJEzzyyCN88MEH3HzzzRgL/dizPJukk/v5/v/eY/GmXMZf9zRzX12JtUDx6rcHGdruMRa9dZzdSfsB+PmdxfgG2Pju7zdYuiyD16+OwHObnsLCQnJzc7GajPhfdikH09KY9e67DB48mKCgID5b+BlHPj6CZzNPLNEW7LaTHJp6iEMHDvPNEBObL53IP/o4nvjqMdq21pM04G66xbZzfx+mT59Oy5Yt2b59OxERrmTHOPRhCpaGoAXEoEU0Rh/dBLV1K8zsA/fMYMfCkTRrnMEPOzLREvLIaWCG/0ti0z870el0xY6QEqKukoRFiDpOKcXCj95l69KFgGtNn4FjH6mWa58eXrxixQr3w/Xy/v3Y+9lMlv4x352wAHTt2hU4U/vQtm1bGjduzI033khiYiJ33HEHeXl5fPjhh0Rl96Vd966kH8+jUxcjsd5ZfL08H6WctGjnT3RUAZ9++zVNm0Vwz8PdMJjzMG53wC+Ql9oUsr359beTAIydffRUBHtYtWoVDcPDGWOzYTKZWLx4MVOnTiU3N5fA8ED8OvvR8JqG3NH+biY89iq5O3LxCPHkxh8LsP/4NA0aRDFixLU8++yzpKWl8d//vsLgwYMxGo189913+Pr6ctlll9G2bVsA/kjYyrHCCLrEtMfb25tta1bz+OOP07NnT+Li4kjTG7m6vYWP13py37IXeaHjOI7Z03hm3pvcOvQmaQ4S9UvV9v2tPjJKSNR1O//+S21fsUQVWgvKdd7qH79Vb9wwRK2dN0cV5OZWUXRFOZ1ONW7cOPfw4n/7ZdaX6oUXXlBLfvnZvW3lypUKUJs2bXJvGzdunIqKilK7du1Se/bsUe+8844C1Is3f60+vH+J+n7KOvXRe58pi8WiZs+erQC1YMECpZRS7dq1UzqdTun1eqXX65VOp1OA0ml6NeSS0Wr6438ppZSyZ2Wp9B/mqJ7Nm6t7+/dXJz76WFkPHTon5t/3/65az2ytMq2uf2MoYVTRjA+nKqWUOnz4sLrssstUYGCgMpvNqnHjxurxxx8v8m/UkiVLVPfu3ZWfn5+yWCyqSZMm6sknn1Tp6elKKaXWfXa5OjA5Qu3YsUP169dPmU0mFeETou7ucoPa/egilbM+5QJ/UkLUvLI+v6WGRYiLQOL2Lfw6dQoAHp9/Qtv+g2jdpz/+4a6mhbysTOxWK2Yvb3LS0ziwcR2ZJ45zdOc2Thw6QLdrR9Jl2DXVFu+4ceOYNWsWP//8Mz4+PqSkpADg5+eHh4cHzTp35f1PppN09AhOvYFcm52HH37YXfuglOKqq65i5cqVfPXVV5hMJrZt28aHH35Ih3adCPIJp/edcfyzYxXjRt/D22+/7a5tMBqNZGZmMmfOHPLz890xrVu3jjvvvJPZ039m37ICrDk2lFOh9/HB/9prMLz7DpZWrQi+5+5i78mgc/1zqU6NUzj9NT8jkYXz7uJZlQTAwMMvwrtfEN3ocpbP+h80KLnprW/fvvz9998lfyP1RvTKSfPmzVm8eDEAK+f8Rtw6V8fE9O93o+xOvLtGlPozEeJiJwmLELVczsk0Fk57h4gmzRg49mESFv7GPwvmseanbwlv3JSgqBj2rPmbwvy8c84NiIziirvvp02/AdUa84cffghAnz59imyfMWMGt99+OxaLhawCK199PYuZMz8nNi6Oa691NaWAK+FZunQpsbGxjBw5ksLCQiIjIxkxYgQjR4zm1/c38960eaxe/xd2u51x48a5r9GvXz9Gjx7NzJkzi1w7NdW1+nSHzm05vmYPTqdi2Te7CGhVAEBOTg4nTpwgISEBk8lEy5Yti5yv11wrLdudRZcR8PCPxuOyR2H5o/SP7EVYx35w6G/Y8Sus/RhaXg1X/hf8o8v9fdQMJvROR5Ftva4dwlrvPwlbakCPjoyf9qJsTnx6NSh3+UJcTGRYsxC12MGEDcx9/SU0vZ5bp7xNYKSrH4jNWsDe9WvYu+Zvju7aTnSrtjS5pDvJe3ez46+lhDduSvsrBldbx9qK2LByBb8sXkJ8aBC3jX2gyL6ShlbPmDGDPt2v5KuXVvDT1jc5mLif3NxcoqOjGTFiBM8++2yJ//8vW7aMvn37kp6ejs5u5svnVtG8azj972h1zrGxsbEcPHiwyLYVR1Yw7s9xvHbZa7QMakmkVyRGvZE/Dv7BkyueZEDcAP7b67/umhicDtjyPSx6AazZcPmz0PVe0OnL/j2afR3Re5cR+mzqOfs2/70a71/yMCkjAL4D4/DtU/6kSIiaJsOahbjIJe/Zxc//e4XoVm258t4H8QkKdu8zmi206NmbFj17Fzmnabde9L7lzuoOtUIO7N0LQHp6BnabDYPR6N53vr+jkg6dIMA7lPdf/4xuV7Qp8/X69OmDUgqnU7F1+VG8/c0odf5rnS3CKwKL3sITK54AQEPD0+hJvj2fQQ0H8d+e/0V/djKi00O7m6DZYFjyEvzxNGz+Foa9DZHty3RNzWDGoJzF7mvboxt7vLeQ+20yXg4PshYcRBU68L0itkrm0hGipknCIkQtpJTiuxcnoDcZuerRpzGaLTUdUqUbeO117H3zDdJtMOujD7jt/ofKdJ7Z4kpsbIWOUo4sXkZKHn99uxvvADPhjfzKfF6TgCasunkVKbkpHMk5QlJOEtmF2XgZvRjReETRZOVsFl8Y/Dq0uQF+eQg+6QvdxkKfCWD2Pv9F9SaM50momrRtwxEvLzJm7sTf5kP2kkSU3YnfoIaStIg6RxIWIWqZwvw8cjPSsdsKsfj61slkBcDbx5cx/7mPae+/z/7UdLauW0PrLl1LPc9odv2zZSu0l3Jk8bRTqw5ccWdLIpsElOtcg85AlE8UUT4VmP8kugvcuxxWvQfLpsD2eTDkTWh6ZYmn6AxmDK4130pMQKIaxWMZ60niR+sIKfAnZ8VRVKET/6saoekkaRF1hyQsQtQCBTk5fHjPLfiHhXMy6Yh7e5dh19ZgVFUvJDyCR598krdefZUffpvPD7/8is7pRAPXS3N91Wkamqad+qrHg0vZtfwoR9YeRKcHnV5DZ9DQ6zX0Bh06gw6DQYfeqMPkaaFBs2YYTQb0Bh25mVYAHPYa6L6nN0Kvh10dcX99BGZdD62ucdXAeAWfc7hmMGNUCpvThklvKrHY4IhwLA9dxrYPl9AgK5jc1ckou5OAa5pI0iLqDElYhKhBTqeDw1s3M+e/zwFg8fElIKIBHQdfTWTT5oTGxddwhFXP09uHe8aO5e8/F1FYaKPQZsNut+FwOE69nDgdDhxOJ06nE6fDid0zCbPdQn6OhnJqKKWhlA6ldIAOlA6FDtCjaYqdq3aec12jueydXytdYDzc+hNs/g4WPAnvXwKXPwcBsaA3g94EeiOe1lwMQI4t/7wJC4B3gB8dHhnM8k9/pMWRKPLWH0PZHATe0BxNL0mLuPjJKCEhaojdZuOHl5/h6M7tAEQ0bsZNk15Dp9cX7Qj6r/9FFWfvO/uwf/+vrM7ad2arpoHeYKSuO7j5H3585QU6DbuGHtfdisPudL1sTjSdhk9gLWlqyzkOvz8G238udnchkPP4bgK9wspUnNPpZMt/5xOU6/p30BFrJOberlLTImotGSUkRC23dOZH7mQFIHnvLt66+eqqv7Cmcc1TE2lYi4c8X6iTSUf4deoUYtu259KRt6LT6Wu2RuV8vEPhhi8gNxVseeCwgd0KjkI2paznmY1v8Cnl+7vydLICoD9kIyMjjYDAc5uchLiYSMIiRA3pMHAYgZFRGC1n/6V/5q/gIp0si7z911/KWgnnFDnkzPY/pr1NxrHkCsV8McjPyeanV1/Eyz+QIQ89ga4c857UqGL6sFi1Qg4ZjdgctjIXs2n9GkKALH0u+Tf58eHyd2mytx1PdHlCRg6Jc53YDfnpEFNCh/ecE7B9LnS+s1xzCFUFSViEqCHB0bEER8dW+3WXzPgIu9Va7detLrv+/ovMY8e4c+pHWLxKGTZcy53ut1LoLCzzOcZ56YAPBcN86NSmO1HZf/DVjq+wOW081vkxLIZa0hQmaod5D0DiauhyN5g8wV4IDqvrqz0fts5xHRfVGSI71GiokrAIUc8YzGbshWV/AF5sjuzYilJO9zpLFzOj3tXXqNBRtp/X8WPJ+Nt9AGh/SXcAJvaYSKvgVkxeM5lVSat4ofsLXBJxSdUELC4uTgdkHHa937/U9dlgAYPJ1fnbYIaYHnD4b7AV1GysSMIiRL1jNJmxFdbdGpb87KyaDqHSmHTlq2E58NEqGhDCzpYpROl07u3XN72eTmGdePHvFxmzcAy3tLiFxzo/VvJkd6Juy8+ANdNgzyLIOQajf4GGlxV/bPoheLutq9alhknCIkQ9YzCZ6nSTkE6vp8klPWo6jErhbhIqYw1Lg7wQAPziQs/ZF+8Xz4yBM/hm5ze8tu41TuSf4JVer5Q6XFrUMfnpMP1KyDwKMd1g1HclJyvgqnEBV0fwGqYr/RAhRF1iMJuxlZKwrFixgmHDhhEZGYmmacydO7fIfu3URG7/fr3++uvuY+Li4s7ZP2XKFPf+gwcPFlvG6tWrK3RfuRnpHD+4H1tBfoXOr43cNSxlTFiyDDkAOO3FL1ug03SMajGK//X5H0sPL2Xcn+PIteWWeT0lcZHLOQEf9oLU3XDvCrj1R2jc//znGMyur3ZpEhJCVDOjyYy9lCah3Nxc2rVrx5133sk111xzzv7k5KKjjObPn8+YMWO49tqiM/NOmjSJu+++2/3Zx8fnnLIWL15Mq1ZnVkwOCgoq033829fPPEJ26gkAWl7at0Jl1Dbl7cNSqHMlKiUlLKf1i+nHtCum8eCSB+k2qxttg9syc9BMjLq6Pz9PveN0wqGV8M/XsGMeoMHN30Nw47KdX4tqWCRhEaKeSdy+BYAhDz5e4jGDBg1i0KBBJe4PDw8v8vnnn3+mb9++xMcXnZnXx8fnnGP/LSgoqNRjysJhs9G230BaXNaX4KjqH31VFco7SsihP52wFL/C89m6hHdhxsAZXP/L9WxO3cyOtB20DWlb8WBF7eKww/rpsPoDSD8IQY2h1yOuFcT9o8teTi2qYZEmISHEBTl27Bi//fYbY8aMOWfflClTCAoKokOHDrz++uvY7ecuWHjVVVcRGhpKr169mDdvXoXj0BuNePr5EdW8FRbvi3s482nlbRJy6lxNO6qUGpbTmgc2Z/XNq4nzjWPcn+PYcGxDxQIVtUN+OqRsgXkPwhtNYP6TEN0N7lgA96+H3o+XL1mBU1Njm6SGRQhR/Vpe2pesU00nleHzzz/Hx8fnnKajBx98kI4dOxIYGMjff//NhAkTSE5O5n//+x8A3t7evPnmm/Ts2ROdTsecOXMYPnw4c+fO5aqrrip3HAajEbut7BOsXQxO17DYnGW7L6W5EhZHYdkSFgAvoxdfDf6KR5Y9wl0L72JSj0kMazSs/MGKmnPyAPzzFfz1huuzyRu6/gdaDYfwNhdevsFSK2pYJGERop7Rm0yl9mEpj88++4xRo0ZhsRSdkOyRRx5xv2/bti0mk4l7772XyZMnYzabCQ4OLnJMly5dSEpK4vXXX69QwqI3GHHUsYRFp+kwaIYy17DkttHDKsBYvhlt/cx+TOs/jUmrJ/H0yqc5kHmA+9rd5+5DI2qxdZ/C76eady3+MPgNaHnVmaacymAwS8IihKh+BqOp0moi/vrrL3bt2sW3335b6rFdu3bFbrdz8OBBmjVrVuIxixYtqlAseqOpziUs4KplKWvC0vfqq0jsfIDuweWfGM6oNzKpxyRifWN575/3+G3/b7QKbsWY1mNoFdyq9AJE9bIXwuIXXH1Uuv4H+j4NFr+quZbB4rpeDZM+LELUM3qjEYetcv7xmT59Op06daJdu3alHpuQkIBOpyM09Nw5Qs4+JiKiYjPU6o1GHPY6mrCUY2r+6AYNMZkr9te1pmnc1eYuvh36LU0CmrAscRmjfh/F5DWTyS7MrlCZogqkH4IZg2DtJzDoNRg4peqSFZAaFiFEzTCYzNgLz/9gz8nJYe/eve7PBw4cICEhgcDAQGJiYgDXkvDff/89b7755jnnr1q1ijVr1tC3b198fHxYtWoVDz/8MLfccgsBAQGAq++LyWSiQwfX+iQ//vgjn332GZ9++mnF7stoqJNLDph0pnItflgZmgU2471+72Fz2Ph6x9e8ueFNFhxcwC8jfsHX5Ft6AaJqKAUbZsLCZ8EjEO78A6KqYdV1g0U63Qohqp/BaCy1D8v69evp2/fMXCan+5qMHj2amTNnAjB79myUUowcOfKc881mM7Nnz2bixIlYrVYaNmzIww8/XKTPCsBLL73EoUOHMBgMNG/enG+//ZbrrruuQvelN9TNGhaj3liuGpbKvvbtrW9H0zTe2fgOQ38cyg3NbqBPdB9aBrVEp0klfbXJPAI/3+9a86fjbXDlf8FSTcmj1LAIIWqCwVR6H5Y+ffqUOvvpPffcwz333FPsvo4dO5Y6Y+3o0aMZPXr0+YMtB1cfljpYw1KOPixVZXSr0QxqOIgPEj5g1s5ZfLT5I4I9guke0Z3ukd25Mu5KzPpK7OQpzlDKNQLoj6ddo39umVP67LSVrZbUsEh6LEQ9U1cf7Po6OKwZXE1CNZ2wAIR6hjKxx0RW3LiCzwZ8xtD4oezJ2MMzK59hwA8DWHxocU2HWPekH4JZN8C8+6HFVTB2VfUnK3BqHhapYRFCVDODyYTT4cDpcKDT153Veg3GujesGVw1LGWdh6U6GHQGuoR3oUt4FwAOZh7kfxv+x+MrHuf9y9+nR4PzLzyp7HZy/voLx8mTeHXrhrFBg+oI++JzZL0rWTF4wE2zoPmQmoulltSwSMIiRD1jMLrm1rDbCjHpPWo4mspTV0cJGXVGrI6af1iUJM4vjjf7vMn4peMZv2w8b/d9m+6R3Ys91pGRwe5uZ/ZpFguRr72K75VXVle4td/JA7B4Imz/GRp0hJGzwbvkkXXVwmCGgsyajYELbBKaMmUKmqYxfvx497aPP/6YPn364Ovri6ZpZGRkXHCZQojKoze5Zk+tayNq9HW0hsVisNSKJqHzMeqMvNH7DTqGduQ/i//DjK0zij0u/dvvAAh7egLNNqxHHxhA2sefVGeotVvKFvi0PxxZB0Pfco0CqulkBWpNDUuFE5Z169bx0Ucf0bZt0cWy8vLyGDhwIE8//XSllSmEqDwGoythqWsPd73BiL0O9s0x6U21uoblNA+DB+/3e587W9/J/zb8j693fH3OMYUHDmBp04bA224jf/Nm7EnJBI25swairWWcTlg3HT4bBH5RcO9f0PkOqC0zDRvMUAt+ByuUsOTk5DBq1Cg++eQT95wKp40fP56nnnqKbt26VVqZQojKYzhdw1LHHu6uPiznLq54sTPrzRdFwgKg1+l5qONDdAjtwJS1U/hpz084nGfWNTI2aEDhgQPYkpNJ+e9/8WjfHp+BA2sw4lpg5VvwZlP47RFoPQJG/wJeQTUdVVEXcw3LuHHjGDJkCP37V15v5fKWabVaycrKKvISQpTudA1L3WsSMtXJPixmvbncTUIrVqxg2LBhREZGomkac+fOLbJfKcXzzz9PREQEHh4e9O/fnz179hQ5Ji4uDk3TirymTJni3r9r1y769u1LWFgYFouF+Ph4nn32WWw2Gx/2/5D+Mf15/u/nuXbetXy942tsThv+N9yAZjKxt+/lFO7dR/ikF9G08q17VKds+cHVXyX3BNw6F656t/rmVikPQ+0YJVTuhGX27Nls3LiRyZMnV1oQFSlz8uTJ+Pn5uV/R0eVcMluIekp/qtOto84lLMY6l4SBK2EpcJTvYZGbm0u7du14//33i93/2muv8c477zBt2jTWrFmDl5cXAwYMoKCg6HUmTZpEcnKy+/XAAw+49xmNRm677TYWLlzIrl27mDp1Kp988gkvvPACXkYv3ur7Fl8N/opY31jeWPcGw34axuK8DeTcMgiAQ5c3Jz3Sp9T5fuqk3DSY9wDMGeMapvzscWjUt/TzaoreBNU823JxyjVKKDExkYceeohFixadszJrRVW0zAkTJhSZNTMrK0uSFiHKoK42CdXVmW4rUsMyaNAgBg0aVOw+pRRTp07l2Wef5eqrrwbgiy++ICwsjLlz53LTTTe5j/Xx8SE8PLzYcuLj44mPj3d/jo2NZdmyZfz111/ube1C2vH25W+z8dhGPtz0IU+seAIPvaLjVTr+brkHNedK3urzFv1ja2BukZqQmwar3oXV01xJwIBXoNtYqO21TLUkYSlXDcuGDRs4fvw4HTt2xGAwYDAYWL58Oe+88w4GgwGHw1F6IZVUptlsxtfXt8hLCFG6MwlLzf8DVJkMJtcoobr2F3tl92E5cOAAKSkpRZrf/fz86Nq1K6tWrSpy7JQpUwgKCqJDhw68/vrr2O0l9xHau3cvCxYsoHfv3ufs6xjWkY+v+Jj3+73P5IFvM3nSSj4d8BkAT698mp/2/FTnfm5F5JyARc/D1Daw5mPoeg88sAG6jyuSrEycOPGcZrjmzZsDcPDgwXP2nX59//3351wyLS2NqKioCo3WPYfeCLVgpFq5alj69evHli1bimy74447aN68OU8++ST6CkxCVRVlCiFKVmf7sBhONXXZ7e65ZuoCs96MtRI7PKakpAAQFhZWZHtYWJh7H8CDDz5Ix44dCQwM5O+//2bChAkkJyfzv//9r8h5PXr0YOPGjVitVu655x4mTZpU7HU1TeOyqMvcny+JuIQ1N69hytopPP/386w8upLnuz+Pn7kKVx2uTkpB2l7Y+Rus/J9rJFC3/0C3ceftVNuqVSsWLz4za7DB4HpMR0dHk5ycXOTYjz/+mNdff73Y2rQxY8bQtm1bjh49euH3UktqWMqVsPj4+NC6desi27y8vAgKCnJvT0lJISUlxb3S65YtW/Dx8SEmJobAwEDAlaSMGDGC+++/v0xlCiEqj949rLmOJSyn++bYbHUqYTHpTVid1T9C4+wm97Zt22Iymbj33nuZPHkyZvOZdYO+/fZbsrOz2bRpE48//jhvvPEGTzzxRJmu4Wn0ZFLPSfRs0JMXV73Idb9cx+Rek+kc3rnS76faKAX7l8GfkyBpo2uETbNBMPjNMo3+MRgMxTbD6fX6c7b/9NNP3HDDDXh7exfZ/uGHH5KRkcHzzz/P/PnzL+h2XBc31YoalkpfS2jatGl06NCBu+++G4DLLruMDh06MG/ePPcx+/btIzU1tbIvLYQoA4Pp1Ey3da2G5XTCUsf6sVT2xHGnH3rHjh0rsv3YsWMl9lcB6Nq1K3a7nYMHDxbZHh0dTcuWLRk5ciRTpkxh4sSJ5e4eMCBuAHOGzaGBdwPGLBzDu/+8W6uWIyizwjz47jb4crirqeemb+CJA3D9zDIPVd6zZw+RkZHEx8czatQoDh8+XOxxGzZsICEhgTFjxhTZvn37diZNmsQXX3yBTldJj/iLsUmoOMuWLSvyeeLEiUycOPG85/z7F760MoUQlUenN6Bpujo3cVxdnRDPpDdRYC9AKVUpQ4AbNmxIeHg4f/75J+3btwdcgxbWrFnDfffdV+J5CQkJ6HQ6QkNLnnnV6XRis9lwOp3lbs6P8I5g+pXTmb51Ou/+8y4fb/6YyZdOZmj80HKVUyP+ehMSZkFuKtjy4Nrp0Pracnem7dq1KzNnzqRZs2YkJyfz4osvcumll7J161Z8fHyKHDt9+nRatGhBjx5n1m6yWq2MHDmS119/nZiYGPbv318pt4feBMoBTgfoaq6bhqwlJEQ9o2kaepMRe2HNTwRVmU73Yalro58segsKhd1px1jGmU9zcnLczfLg6mibkJBAYGAgMTExjB8/npdffpkmTZrQsGFDnnvuOSIjIxk+fDgAq1atYs2aNfTt2xcfHx9WrVrFww8/zC233OKe2PPrr7/GaDTSpk0bzGYz69evZ8KECdx4440YK9gkp9fpuaftPXQI7cCdf9zJhL8msDZ5LQ91fIggj1o2mZpSrgUKN30D66dDaEvoNBo6joagRhUq8uy+KG3btqVr167Exsby3XffFalJyc/PZ9asWTz33HNFzp8wYQItWrTglltuqdg9lUTv+mMAh00SFiFE9TIYTXVulNDZfVjqEtOph0WBo6DMCcv69evp2/fMvB6n+6OMHj2amTNn8sQTT5Cbm8s999xDRkYGvXr1YsGCBe6pJcxmM7Nnz2bixIlYrVYaNmzIww8/XKRfi8Fg4NVXX2X37t0opYiNjeX+++/n4YcfvuB77hLehYRbE/hh9w+8m/AuCw8tpHdUb+5tdy/xfvGlF1DV7IWw9GX4v7dBb3YNT+4+rtIv4+/vT9OmTYsknwA//PADeXl53HbbbUW2L1myhC1btvDDDz8AuEdeBQcH88wzz/Diiy9WLJDTv3eOQjBWzpQmFSEJixD1kMFkqnN9WAx1NGEx610dXK0OKz74lHK0S58+fc47TFjTNCZNmlTiiJ6OHTuyevXq817jxhtv5MYbbyxTPBWh1+m5sfmNDIgbwEebP+KrHV/x+4HfuaftPYxuNRpfUw1MZeF0wr4l8MfTkLYHOo+BQa+BvmoepTk5Oezbt49bb721yPbp06dz1VVXERISUmT7nDlzyM/Pd39et24dd955J3/99ReNGlWs1gcoWsNSgyRhEaIeMhhNdXaUUF2rOTqdsNT2FZurir/FnycveZJRLUbx9Y6v+WXtQmyfxdGmU0O6DI7HP9Sz6oPIOwnrP4MNMyEzEaK6wL0rILxNpV7mscceY9iwYcTGxpKUlMQLL7yAXq9n5MiR7mP27t3LihUr+P333885/99JyenBLS1atMDf37/igbkTlpr9HZSERYh6qC5OY19Xm4ROJyzlnZ6/ronyieLJS56kWVYnjv6jY/fq4+xefZy2l0fR+rIGmD2NePqaKu169kIHhzYfI3nhXC6xTcGkK4C217v6qER1qZLZaY8cOcLIkSNJS0sjJCSEXr16sXr16iI1KZ999hlRUVFceeWVlX79Ep3dJFSDJGERoh4ymEx1rnOqe5RQHRvWXN9rWP7Ny8MTKOCyh6Ip2G/gn4WH2bzkCAA+QRbi24fQuFMoYQ19yz2qym5zcHjbSfZuOM7BzanYrA6gObHdxxF97Z3gHVJqGRdi9uzZpR7zyiuv8Morr5SpvNKaBstMmoSEEDXFYDLVuZqIul7DUpnT81/MzGYjUIBDs9NlSBNa927AsQNZ2AudHN2dzu51x9j0ZyLegWaimwdiMOowmPT4BlvwCfJA04HZw4jRrCcnvYCstAJyM6ycSMwmaU8GtgIHgZFedLgyhsgGTuZOO4QjrEOVJyu1mk5qWIQQNURvrHudbuvqsGZ3wlKJ0/NfzDwsFiCbfKuriczD20Rcm2AAGncK5dIbm5K8J4O9G45z7GAWTqfCVmAn56QVp/Pc2gZNp+HpayIg3JOOV8YQ3z6UwEgvAApOHAfAaSt5DaV6QZqEhBA1xWA01rkHe12tYTk9rFlqWFw8Ti0LkF9Q/PdDp9No0CyABs0Cimx3OpzkZhailKIw347N6sTT14R3oBm9vvgZYXUm17Uc9T5hkSYhIUQNMRhNWPPzajqMSqU/tUhcXevDYjG45r2QPiwuHqfmirFay/f90Ol1+ASWbw4Rvfl0wlK+pQbqnFoySqjS1xISQtR+dbEPi6Zpp0Y/1a37OnviOAFeFg8ArNaq/znrTK7vvdNe32tYakeTkCQsQtRDepOpzk3ND65+LHWthkVGCRXl6eGad8VaDX2wNJ0OHTYcNmeVX6tWqyVNQpKwCFEP1cWp+aFu1hzpNB1GnVFqWE7xOtUkVGitnloPvWbHYZcmIQBquB+VJCxC1EOuB3vd+4u9LtawgKuWRWpYXPQGPQ7Njq2wOhOWel7DYnDV8lHDI9UkYRGiHtIbTdjq2LBmAL3RUOeGa4MrYZFRQmc4dNWXsOg0hyQspzp+Y6/ZWj5JWISohwxGI446+GCvyzUsBTX8sKhNnHo79moauaPXOXDaK2G22IuZ3gA6gyQsQojqZzCZpQ/LRcSkN0mT0Fmcegf2wuqp9dBLDYuLwQNskrAIIaqZwWSsu6OE6mDCYjFYpEnoLE69HUdh9dR66HVOHPW8zy3g6sciNSxCiOpmMJlRTifOOvYvsd5orJM1Rya9SRKWszhNNpzWyl8tuTh6nQOHo543CYGrH4skLEKI6nZ6Gvu6Nj2/wVg3a1ik021RyuRAWavn8aXTKZx1K6+vGGPNJywyNb8Q9ZDB6JpXYduyxXj4+GIwmTEYjRhMZvRGIzqDAYPRiN5gRG80ojcYTn11vdd0tfNvHb2x7na6lT4sZzE7IMdcLZfS65w46vlEt4CrhqWG+7BIwiJEPeQfFo7RbGHJjI8qdL5Orz+TzJxOaNzJzVkJzr8/F5MAGU4lSKffn12ewWzGaDJjMJsxmEwYzWYMJrPrq9mMTqcvEpfeYKSwjq2RBKdGCcnEcW4GDx2k6Us/sBLodQqn9LmtFU1CkrAIUQ8Fx8Tx4Bc/4HQ4sNsKsReeeTnsNpx2O3abDYfNhsNuw2G3n3lvK+Hz6ff//my3Yc2zuvfZT2132u3u92d/RpW9v4DeYCiS1ORlZhIcE1d137gaYtabyS7Mrukwag2zpwF7obFarqXTKxyO6ukvU6tJwiKEqEk6vR6T3gPTqQXlappSCqfD4U527LZC7FYrNqsVe+G/vlqt2Aqt5+yPbtWmpm+j0nkaPVl7YC1vrn8Tg86AUWc889KfeX96n0FnQK/p0ev0GDQDep0evaYvsl2v6THqjCXu+3cZmlZ7Htqe3mby7NXVJAR1bD3NiqkFo4QkYRFC1Bqapp1qDjJALUmiaoPBDQez5cQWliUuw+a0YXPasDvtZ746bNhV1Xa00Gm6IonMvxMao96IWW92v0x6k+vnqenRoXO/P/ur1+EIgle2w+FZgDU6FTQNTXP9Hpz+ivvzmW3HEjOJcAaQl5+Pp0fV/p7o9ZCTZWH3nHnubUVytyJ53JkPEZEOvL1V0e16E3j4g8UfTF6uVZB1RtDpQTldtYvKCaiSP/PvGsizAigpsMraLn1YhBBCnE+X8C78cNUP5z3GqZxFkhiHcuBwOnAoB3an3b2tuH2nP9uV/ZzPxR7ntJ+zz+a0UWAvoNBZSIG9AJvThlM5cSonSinsTjuFFOJ0OnHi2ha8tTMA+jwLKtkDlOZ6HCtAnXpQKg3UqcemAtDwVaFk+51Ab6j6zt++gQZ2p4SxaFH5zmtmWUp//3eqJqia0uTKGr28JCxCCFEH6DQdJr0J0+mVdS8CczZtwL+FB/1Gt6zpUEp0yf230DEv99QndaaCQ6lTb5V71+n+V79P34vdcwTc8VjRPll2KxRkQkEGFOaC037q5XDVamg6XFVKulOftX99PrXf7ayyi/T9upDt//4OnLUhtGZ/TpKwCCGEqBE6vYazlk/Kpul0GL19ynWO3mRCaTqw+J270yeskiKrf2rnZApCCCHqvIshYakInV7D6ax791XTJGERQghRI3R6XZ1MWDSNOnlfNU0SFiGEEDXCVcNS92Zl0+k1VDnmExJlIwmLEEKIGqGvq01Curp5XzVNEhYhhBA1QqfX6uRKyJpOQ0kflkonCYsQQoga4erDUveahCRhqRqSsAghhKgRdXWUkKaTPixVQRIWIYQQNaLOJiwassJzFZCERQghRI2os8OapUmoSkjCIoQQoka4RtPUvaoInSZNQlVBEhYhhBA1orxNQitWrGDYsGFERkaiaRpz584t8dj//Oc/aJrG1KlTi91vtVpp3749mqaRkJDg3r5r1y769u1LWFgYFouF+Ph4nn32WWw2W5njlBqWqiEJixBCiBpR3oQlNzeXdu3a8f7775/3uJ9++onVq1cTGRlZ4jFPPPFEsfuNRiO33XYbCxcuZNeuXUydOpVPPvmEF154ocxxatq/1hYUlUIWPxRCCFEjyjvT7aBBgxg0aNB5jzl69CgPPPAAf/zxB0OGDCn2mPnz57Nw4ULmzJnD/Pnzi+yLj48nPj7e/Tk2NpZly5bx119/lTlOqWGpGlLDIoQQ/9/e/cdUVf5xAH+fcy9dMbkaBEsF1AnhjzINl1GWv0hx6bBaMzJE5myWLksrQ//ASqe27+ZQl2KZLtN0la3mj5gOneSM+BEOr6npoCGomKZcta5wz+f7B3AVA7lc7+FcDu/Xdlf3/Hju8+yT3bfPc+45ZAjVovr1IYGapiE1NRXvvfceBg8e3OwxFy5cwKxZs7BlyxZ07dq11TZPnz6Nn376CaNGjfK6H4rKhx/qgYGFiIgM4e+fNa9cuRJWqxVvvfVWs/tFBDNmzMDs2bMxfPjwu7b11FNPoUuXLoiNjcUzzzyDjz76yOt+qCo4w6IDBhYiIjKEP2/NX1RUhKysLGzevBmKojR7zJo1a+B0OpGRkdFqezt27EBxcTG2bduG3bt343//+5/XfVEUhdew6ICBhYiIDOHPW/Pn5eWhuroa0dHRsFqtsFqt+PPPP7FgwQL07dsXAJCbm4sjR47AZrPBarUiJiYGADB8+HCkpaU1aS8qKgqDBg1CSkoKVqxYgSVLlsDtdnvVF17Dog9edEtERIbw55JQamoqEhMTm2ybMGECUlNTkZ6eDgBYvXo1li5d6tlfVVWFCRMmYMeOHRgxYkSLbWuahtraWmiaBovF0mpfFIVLQnpgYCEiIkOoFgUQQNMEqtr8Ms7trl27htOnT3vel5WVoaSkBKGhoYiOjkZYWFiT44OCgvDQQw8hLi4OABAdHd1kf7du3QAA/fv3R2RkJABg69atCAoKwqOPPgqbzYbCwkJkZGRg6tSpCAoK8mpciqqAecX/GFiIiMgQFkt9SNHcGlS19ZmLwsJCjBkzxvN+/vz5AIC0tDRs3rzZL32yWq1YuXIlTp06BRFBnz59MHfuXLzzzjtet8ElIX0wsBARkSFUS/1llJpbAC8mL0aPHt2mW96Xl5ffdX/fvn3/097UqVMxdepUrz+jOSqf1qwLXnRLRESGUD0zLCb7clcAMd8jkgzHwEJERIYwa2BRuSSkCwYWIiIyxK0lIXNNRygKA4seGFiIiMgQZp1hUVTeOE4PDCxERGQI0wYW3odFFwwsRERkiMYlIbfZloRUBRqnWPyOgYWIiAzROMNittkIVa2/IR5/2uxfDCxERGQI0y4JNXyzmi2IGY2BhYiIDGHewNIwc2SuYRmOgYWIiAxhMfHPmgHOsPgbAwsRERmicYbFbboZlvp/agwsfsXAQkREhjDtkpDCJSE9MLAQEZEhmjz80ERUlUtCemBgISIiQ9yaYTHZNSwMLLpgYCEiIkOYdUnIMy4GFr9iYCEiIkOYNrCo5hyX0e4psKxYsQKKouDtt9/2bNuwYQNGjx4Nu90ORVFw5cqVVttZt24dhgwZArvdDrvdjoSEBOzdu/deukZERAHu1he7yZaETHoHX6P5HFgKCgqQnZ2NIUOGNNl+48YNJCUlYdGiRV63FRkZiRUrVqCoqAiFhYUYO3YskpOT4XA4fO0eEREFOMWkMxGcYdGH1ZeTrl27hmnTpuGzzz7D0qVLm+xrnG05ePCg1+1Nnjy5yftly5Zh3bp1+OWXXzB48GBfukhERAFOURSoFsV0X+yewMIZFr/yaYZlzpw5eP7555GYmOjv/sDtdmP79u24fv06EhISWjzO5XKhpqamyYuIiDoWMwYWLgnpo80zLNu3b0dxcTEKCgr82pHS0lIkJCTg33//Rbdu3fD9999j0KBBLR6/fPlyfPjhh37tAxERtS/VosJtsmtYuCSkjzbNsFRUVGDevHnYunUrunTp4teOxMXFoaSkBPn5+XjjjTeQlpaG48ePt3h8RkYGrl696nlVVFT4tT9ERKQ/M86w8GfN+mjTDEtRURGqq6vx+OOPe7a53W4cOnQIa9euhcvlgsVi8akj9913H2JiYgAA8fHxKCgoQFZWFrKzs5s93mazwWaz+fRZREQUGMwYWHjjOH20KbCMGzcOpaWlTbalp6djwIABWLhwoc9hpTmapsHlcvmtPSIiCjz1gYVLQtS6NgWWkJAQPPLII0223X///QgLC/NsP3/+PM6fP4/Tp08DqL82JSQkBNHR0QgNDQVQH3xeeOEFzJ07F0D98s7EiRMRHR0Np9OJbdu24eDBg8jJybnnARIRUeBSLarpvti5JKQPn37WfDfr169vcjHss88+CwDYtGkTZsyYAQA4c+YM/vrrL88x1dXVmD59Os6dO4fu3btjyJAhyMnJwXPPPefv7hERUQCxmHlJyGTjMto9B5Y777eyZMkSLFmy5K7nlJeXN3m/cePGe+0GERF1QGa8hkVVG55CzRkWv+KzhIiIyDD1S0Imu4aFS0K6YGAhIiLDmHOGhUtCemBgISIiw5gxsCicYdGF3y+6JSIi8pZqUXAy/zxsXa2wWFWoVgUWq+p5qRYFliAVFosC9fbtjcdZVFiCFKiWxn1Kw/6Gf7eonotg221MnmcJmWupy2gMLEREZJi+jz4I1406nD35NzS3wF2rwV2nwe3W4K4TaHXaPc/AqKoCtSH0tBiK/hN2GkJSUEMost4emJqef/s+a5AKReGSkB4YWIiIyDBDE6MxNDH6rseIJvVhpjHI1Ao0d0OwqWvYXqdBu/N9wznNbq+9FYpuHVP/vs7lhutGbbOf01xbLbHa/HczVWJgISKiAKeoCixq/dJQoBFNbgWfxtmhOg0QoHtEsNHdMxUGFiIiIh8pqgKraoE1CADzia4CL64SERER3YGBhYiIiAIeAwsREREFPAYWIiIiCngMLERERBTwGFiIiIgo4DGwEBERUcBjYCEiIqKAx8BCREREAY+BhYiIiAIeAwsREREFPAYWIiIiCngMLERERBTwTPO0ZhEBANTU1BjcEyIiIvJW4/d24/d4S0wTWJxOJwAgKirK4J4QERFRWzmdTnTv3r3F/Yq0Fmk6CE3TUFVVhZCQECiK4tU5NTU1iIqKQkVFBex2u849pHvFenUcrFXHwnp1LGarl4jA6XSiV69eUNWWr1QxzQyLqqqIjIz06Vy73W6KoncWrFfHwVp1LKxXx2Kmet1tZqURL7olIiKigMfAQkRERAGvUwcWm82GzMxM2Gw2o7tCXmC9Og7WqmNhvTqWzlov01x0S0RERObVqWdYiIiIqGNgYCEiIqKAx8BCREREAY+BhYiIiAKe6QPLqVOnkJycjAcffBB2ux0jR47EgQMHPPsvXbqEpKQk9OrVCzabDVFRUZg7d+5dn0lUXl6OmTNnol+/fggODkb//v2RmZmJmzdvtseQTEuPWgHA5cuXMW3aNNjtdvTo0QMzZ87EtWvX9B6O6bVWr6NHjyIlJQVRUVEIDg7GwIEDkZWVdc/tUtvpVSsA2L17N0aMGIHg4GA88MADmDJlik6j6Dz0rBcAuFwuDB06FIqioKSkRIcR6MP0gWXSpEmoq6tDbm4uioqK8Nhjj2HSpEk4f/48gPo75CYnJ+PHH3/EqVOnsHnzZuzfvx+zZ89usc0TJ05A0zRkZ2fD4XBg1apVWL9+PRYtWtRewzIlPWoFANOmTYPD4cC+ffuwa9cuHDp0CK+//np7DMnUWqtXUVERIiIi8NVXX8HhcGDx4sXIyMjA2rVr76ldaju9avXdd98hNTUV6enpOHr0KA4fPoxXX321PYZkanrVq9H777+PXr166TkEfYiJXbx4UQDIoUOHPNtqamoEgOzbt6/F87KysiQyMrJNn/XJJ59Iv379fO5rZ6dXrY4fPy4ApKCgwLNt7969oiiKVFZW+qfznZCv9XrzzTdlzJgxfm+XWqZXrWpra6V3797y+eef+7W/nZ1e9Wq0Z88eGTBggDgcDgEgv/32mz+63S5MPcMSFhaGuLg4fPnll7h+/Trq6uqQnZ2NiIgIxMfHN3tOVVUVdu7ciVGjRrXps65evYrQ0FB/dLtT0qtWR44cQY8ePTB8+HDPtsTERKiqivz8fL+Po7PwpV5A639OfG2XWqZXrYqLi1FZWQlVVTFs2DD07NkTEydOxLFjx/QYRqehV70A4MKFC5g1axa2bNmCrl27+rvr+jM6MemtoqJC4uPjRVEUsVgs0rNnTykuLv7Pca+88ooEBwcLAJk8ebL8888/Xn/GH3/8IXa7XTZs2ODPrnc6etRq2bJl8vDDD/9ne3h4uHz66ad+7X9n4229Gh0+fFisVqvk5OT4tV1qnR61+vrrrwWAREdHy7fffiuFhYWSkpIiYWFhcunSJT2G0WnoUS9N0yQpKUk+/vhjEREpKyvjDEt7+OCDD6Aoyl1fJ06cgIhgzpw5iIiIQF5eHn799VdMmTIFkydPxrlz55q0uWrVKhQXF+OHH37AmTNnMH/+fK/6UllZiaSkJLz88suYNWuWHsPt0AKpVtQ6PeoFAMeOHUNycjIyMzMxfvz4Fj+/re12ZkbXStM0AMDixYvx0ksvIT4+Hps2bYKiKPjmm290G3dHZXS91qxZA6fTiYyMDD2HqS8j05Kvqqur5ffff7/ry+Vyyf79+0VVVbl69WqT82NiYmT58uUttp+XlycApKqq6q79qKyslNjYWElNTRW32+2XsZmN0bXauHGj9OjRo8m22tpasVgssnPnznsfoMnoUS+HwyERERGyaNGiVj/f1/8OOiOja5WbmysAJC8vr8n2J554wqvzOxuj65WcnCyqqorFYvG8AIjFYpHp06f7dax6sRobl3wTHh6O8PDwVo+7ceMGgPpfl9xOVVXP3w6a07jP5XK1eExlZSXGjBnj+VvFnZ9B9YyuVUJCAq5cuYKioiLP+m9ubi40TcOIESO8GkNn4u96ORwOjB07FmlpaVi2bJnf2iXjaxUfHw+bzYaTJ09i5MiRAIDa2lqUl5ejT58+bRlKp2B0vVavXo2lS5d63ldVVWHChAnYsWNHx/l/odGJSU8XL16UsLAwefHFF6WkpEROnjwp7777rgQFBUlJSYmIiOzevVu++OILKS0tlbKyMtm1a5cMHDhQnn76aU87+fn5EhcXJ2fPnhURkbNnz0pMTIyMGzdOzp49K+fOnfO8yDd61UpEJCkpSYYNGyb5+fny888/S2xsrKSkpLT7GM3Em3qVlpZKeHi4vPbaa03+jFRXV3vaubNe3rRLbaNXrURE5s2bJ71795acnBw5ceKEzJw5UyIiIuTy5cvtPk6z0LNet+uI17CYOrCIiBQUFMj48eMlNDRUQkJC5Mknn5Q9e/Z49ufm5kpCQoJ0795dunTpIrGxsbJw4UL5+++/PcccOHBAAEhZWZmIiGzatEkANPsi3+lRKxGRS5cuSUpKinTr1k3sdrukp6eL0+lsx5GZU2v1yszMbPbPSJ8+fTzHNFev1tqlttOrVjdv3pQFCxZIRESEhISESGJiohw7dqwdR2ZOetXrdh0xsCgiIu0zl0NERETkG154QURERAGPgYWIiIgCHgMLERERBTwGFiIiIgp4DCxEREQU8BhYiIiIKOAxsBAREVHAY2AhIiKigMfAQkRERAGPgYWIiIgCHgMLERERBTwGFiIiIgp4/wfmlX8kSwTsrwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for c in [21,61]:\n",
    "    for u in countyUnitList[c]:\n",
    "        if u in borderUnits:\n",
    "            plotPoly(unitGeom[u])\n",
    "            plotCenter(u,unitGeom[u])\n",
    "print(\"flagging border-stringy near Sandusky.  May want to avoid surrounding these\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "1ed73500-47c8-4c15-9552-3f417fb89ebf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "also, we will not surround [1081] as their neighbors lack interior connections\n"
     ]
    }
   ],
   "source": [
    "borderKeepers = [1081]\n",
    "print(\"also, we will not surround\",borderKeepers,\"as their neighbors lack interior connections\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "3f3d148e-77e7-45e2-9ccf-00e329f3ef1a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Redo tentative set / list of border units. Numbered units have zero nonborder neighbors; will be surrounded next block\n",
      "'pop' shows pop/aDP for pop/aDP > 0.5 in a border unit\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Redo tentative set / list of border units. Numbered units have zero nonborder neighbors; will be surrounded next block\")\n",
    "print(\"'pop' shows pop/aDP for pop/aDP > 0.5 in a border unit\")\n",
    "surroundedBorderUnits = list()\n",
    "for u in borderUnits:\n",
    "    plotPoly(unitGeom[u])\n",
    "    if len(set(unitNbrs[u]).difference(set(borderUnits)) ) == 0 and u not in borderKeepers:\n",
    "        plotCenter(u,unitGeom[u],9)\n",
    "        surroundedBorderUnits.append(u)\n",
    "    if unitPop[u] > 0.35 * aDP:\n",
    "        plotCenter(\"pop\"+str(r3(unitPop[u]/aDP)),unitGeom[u],8)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "dfad82bb-28e4-4e3b-9098-aeca4cdecc71",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "we will collapse unit 1019 into unit 979\n",
      "we will collapse unit 12 into unit 1420\n",
      "we will collapse unit 14 into unit 1421\n",
      "we will collapse unit 29 into unit 1421\n",
      "we will collapse unit 30 into unit 1409\n",
      "we will collapse unit 49 into unit 1239\n",
      "we will collapse unit 70 into unit 5360\n",
      "we will collapse unit 91 into unit 1282\n",
      "we will collapse unit 3216 into unit 3218\n",
      "we will collapse unit 3228 into unit 3234\n",
      "we will collapse unit 193 into unit 1472\n",
      "we will collapse unit 209 into unit 1188\n",
      "we will collapse unit 5365 into unit 5366\n",
      "we will collapse unit 5367 into unit 1439\n",
      "we will collapse unit 249 into unit 848\n",
      "we will collapse unit 268 into unit 1132\n",
      "we will collapse unit 350 into unit 918\n",
      "we will collapse unit 351 into unit 918\n",
      "we will collapse unit 2532 into unit 2541\n",
      "we will collapse unit 2535 into unit 2537\n",
      "we will collapse unit 3570 into unit 3579\n",
      "we will collapse unit 528 into unit 1421\n",
      "we will collapse unit 3764 into unit 3763\n",
      "we will collapse unit 2797 into unit 2796\n",
      "we will collapse unit 2921 into unit 2932\n",
      "we will collapse unit 882 into unit 897\n",
      "we will collapse unit 2931 into unit 2933\n"
     ]
    }
   ],
   "source": [
    "surrounderBorderUnits = list()\n",
    "for u in surroundedBorderUnits:\n",
    "    candidates = list()\n",
    "    for uu in set(unitNbrs[u]).difference(set(surroundedBorderUnits)):\n",
    "        candidates.append(uu)\n",
    "    if len(candidates) == 0:\n",
    "        print(\"ERROR - unit\",u,\"still appears surrounded by surroundees\")\n",
    "    else:\n",
    "        uuDists = [unitCP[u].distance(unitCP[uu]) for uu in candidates]\n",
    "        uuu = candidates[uuDists.index(np.min(uuDists)) ]\n",
    "        print(\"we will collapse unit\",u,\"into unit\",uuu)\n",
    "        surrounderBorderUnits.append(uuu)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "1f6090c3-e394-4770-beef-b1b95f6a8435",
   "metadata": {},
   "outputs": [],
   "source": [
    "countyUnitList = [list() for c in range(nCounties) ]\n",
    "for u in range(nUnits):\n",
    "    countyUnitList[countyNo[unitTractList[u][0]]].append(u)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "4db9ba9b-cb0c-4a6e-8ebe-284f3e0b78c5",
   "metadata": {},
   "outputs": [],
   "source": [
    "for u in surrounderBorderUnits:\n",
    "    if u in surroundedBorderUnits:\n",
    "        print(\"uhoh, we named\",u,\"as a surrounder but it was surrounded\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "3cf86982-9153-4e34-abde-2016afcb2e31",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "prior to surround, we have 5710 5710 units\n",
      "absorbing surrounded border units ...\n",
      "we now have 5683 total units.\n"
     ]
    }
   ],
   "source": [
    "print(\"prior to surround, we have\",nUnits,len(unitPop),\"units\")\n",
    "oldList = [unitTractList[u].copy() for u in range(nUnits)] #safekeeping\n",
    "print(\"absorbing surrounded border units ...\")\n",
    "for u in range(nUnits):\n",
    "    if u in surroundedBorderUnits:\n",
    "        uu = surrounderBorderUnits[surroundedBorderUnits.index(u)]\n",
    "        oldList[uu] += oldList[u]\n",
    "        oldList[u] = list()\n",
    "        \n",
    "unitTractList, unitPop, oldUnitNo = list(), list(), list()\n",
    "for u in range(nUnits):\n",
    "    if u not in surroundedBorderUnits:\n",
    "        oldUnitNo.append(u)\n",
    "        unitTractList.append(oldList[u])\n",
    "        unitPop.append(np.sum([tractPop[b] for b in oldList[u] ]))\n",
    "nUnits = len(unitPop)\n",
    "print(\"we now have\",nUnits,\"total units.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "3edc4190-01a7-424d-9a46-a643cdfac213",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "updating reverse vtd assignments ...\n",
      "state pop = 11799448 = 11799448\n",
      "and reconstitute unit nbr topology\n",
      "we now have 5683 total units. Rebuild neighbor lists\n",
      "rebuilding geom for unit 0\n",
      "rebuilding geom for unit 500\n",
      "rebuilding geom for unit 1000\n",
      "rebuilding geom for unit 1500\n",
      "rebuilding geom for unit 2000\n",
      "rebuilding geom for unit 2500\n",
      "rebuilding geom for unit 3000\n",
      "rebuilding geom for unit 3500\n",
      "rebuilding geom for unit 4000\n",
      "rebuilding geom for unit 4500\n",
      "rebuilding geom for unit 5000\n",
      "rebuilding geom for unit 5500\n"
     ]
    }
   ],
   "source": [
    "print(\"updating reverse vtd assignments ...\")\n",
    "tractUnitNo = [-999 for t in range(nTracts)]  #need to reset after surrounds\n",
    "for u in range(nUnits):\n",
    "    for v in unitTractList[u]:\n",
    "        tractUnitNo[v] = u\n",
    "print(\"state pop =\",np.sum(tractPop),\"=\",np.sum([np.sum([tractPop[v] for v in unitTractList[u] ]) for u in range(nUnits)]) )\n",
    "\n",
    "print(\"and reconstitute unit nbr topology\")\n",
    "oldNbrs = [unitNbrs[u].copy() for u in range(len(oldList)) ]\n",
    "unitNbrSet = [set() for u in range(nUnits)]\n",
    "print(\"we now have\",nUnits,\"total units. Rebuild neighbor lists\")\n",
    "for u in range(nUnits):\n",
    "    oldU = oldUnitNo[u]\n",
    "    for oldUU in oldNbrs[oldU]:\n",
    "        if oldUU in oldUnitNo:  #this will skip the surrounds\n",
    "            newUU = oldUnitNo.index(oldUU)\n",
    "            unitNbrSet[u].add(newUU)\n",
    "unitNbrs = [list(unitNbrSet[u]) for u in range(nUnits)]\n",
    "      \n",
    "unitGeom = list()\n",
    "for u in range(nUnits):\n",
    "    if u%500 == 0:\n",
    "        print(\"rebuilding geom for unit\",u)\n",
    "    geo = tractGeom[unitTractList[u][0]]\n",
    "    for b in unitTractList[u]:\n",
    "        if b != unitTractList[u][0]:\n",
    "            geo = geo.union(tractGeom[b])\n",
    "    unitGeom.append(geo)\n",
    "\n",
    "unitCP = [unitGeom[u].centroid for u in range(nUnits)]\n",
    "unitPop = [np.sum([tractPop[v] for v in unitTractList[u] ]) for u in range(nUnits)]\n",
    "\n",
    "countyUnitList = [list() for c in range(nCounties) ]\n",
    "for u in range(nUnits):\n",
    "    countyUnitList[countyNo[unitTractList[u][0]]].append(u)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "6e277245-da0e-4d1b-9405-b531fe542406",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "spot check - do neighbor lists still look spatially correct?\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"spot check - do neighbor lists still look spatially correct?\")\n",
    "u = 212 #nUnits - 350\n",
    "for v in unitTractList[u]:\n",
    "    plotPoly(tractGeom[v],2)\n",
    "for uu in unitNbrs[u]:\n",
    "    plotPoly(unitGeom[uu], 0.2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "1257f802-1f75-46bb-adcf-62196948966a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "and total vtds assigned =  8934 + skips 7 vs total VTDs 8941\n",
      "total pop =  11799448 vs vtd-summed 11799448\n"
     ]
    }
   ],
   "source": [
    "print(\"and total vtds assigned = \",np.sum([len(unitTractList[u]) for u in range(nUnits) ]),\"+ skips\",len(skipList),\"vs total VTDs\",nVTDs)\n",
    "print(\"total pop = \",np.sum(unitPop),\"vs vtd-summed\",np.sum(tractPop) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "37df254c-38b2-4eae-931e-044e0f8fc9c5",
   "metadata": {},
   "outputs": [],
   "source": [
    "unitCountyNo = [countyNo[unitTractList[u][0]] for u in range(nUnits)] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "e0545c19-3336-4bad-9acf-5eb90106ff6c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here are the unsplittable units, above 0.14 of aDP or a corner border unit\n",
      "9 147110   starts in county 56\n",
      "98 273926   starts in county 47\n",
      "111 190474   starts in county 76\n",
      "149 335721   starts in county 30\n",
      "187 374054   starts in county 17\n"
     ]
    }
   ],
   "source": [
    "unsplittableUnits = list()  \n",
    "minSplitRatio = 0.14  #this will preserve Akron and Dayton, not Parma or Canton\n",
    "print(\"Here are the unsplittable units, above\",minSplitRatio,\"of aDP or a corner border unit\")\n",
    "for u in range(nUnits):\n",
    "    if (unitPop[u] < maxDistrictPop and unitPop[u] > minSplitRatio * aDP ):\n",
    "        unsplittableUnits.append(u)\n",
    "        print(u, r3(unitPop[u]),\"  starts in county\",unitCountyNo[u])\n",
    "#print(\"and FYI, which ones are 0.4 - 0.5 aDP?\")  #this is FYI for 99seat maps only\n",
    "#for u in range(nUnits):\n",
    "#    if unitPop[u] < 0.5*avgDistrictPop and unitPop[u] > 0.4 * avgDistrictPop:\n",
    "#        print(\"   \",u, r3(unitPop[u]),unitCountyNo[u])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "f25dfc14-0345-44a9-9ea9-bcaeeef0741a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "now re-ID the border units ...\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"now re-ID the border units ...\")\n",
    "borderUnits = list()\n",
    "for c in borderCounties:\n",
    "    for u in countyUnitList[c]:\n",
    "        if unitGeom[u].intersects(simpleMAP.exterior) and c not in barredCounties:\n",
    "            borderUnits.append(u)\n",
    "            plotPoly(unitGeom[u])\n",
    "plt.show()\n",
    "onBorder = [0]*nUnits\n",
    "for u in range(nUnits):\n",
    "    if u in borderUnits:\n",
    "        onBorder[u] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "846bd96c-9b8c-4040-999a-289b818367ab",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lets ID borderUs near Sandusky Bay, in case there are any we want to drop\n"
     ]
    },
    {
     "data": {
      "image/png": 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A4DF2LIpeD4AhMBBDYGC5xCqEqNlk8UMharC09etJ/n4Zvs89i6F27RKdm33sOABOPXuUR2hCCFGAJCxC1FDZJ04Q89LLOPfvX6qy+YaQEOBq6X0hhChP0iUkRDVw8fhRUuPjOLBxPRaLhdEz30BXRGXZqGHDUfR6/Ge/WarnNATWQuvuTt6F86U6XwghSkISFiFuc5cvnGPZy88W2Hb2YAT12na44Tn5Y+3VvLwiK9beiCU7G3NyMlp3j1KdL4QQJSFdQkLc5hxc3Qo8Ntg74OLtc9NzFEXB5/nnATg9YgRJK1Zgyc0t9nNaMjNJ+Gw+qCr2rVqWOGYhhCgpmdYsRDUQfzaKjKRE7F1c8QwMKrI7KF/28RPEvPgi2ceO4di5M7U/+9Q24+dG8uIucWb0aEwJCXhOmoTP9Gll8AqEEDWVTGsWogbxDg7BOzikxOfZNWpIyMofSfnlF6KffY6cyEjsGje+4fFZBw9ycfrToKrU+319iWcWCSFEaUmXkBACc1Iyil6PITj4xsekZxD9wgw09nbUXvC5JCtCiAolCYsQgszdu7Fv3RqNvX2h+7MOHiJq1EhMMTH4v/UWdk2aVHCEQoiaThIWIQSm+Hj0/n6F7jOnZ3Du4YfROjkT8vNP2IeGVnB0QgghCYsQNZ45PZ2cU6fQ16pV6P5Lb7+NajIROO+Tm3YZCSFEeZKERYgaLuall0BVcbv77uv2ZR04QPIPP+D7/HPo/QpvgRFCiIogCYsQNZhqNpO2/ne8pkxBHxBQYF/W/v1EP/scxsaNcbvnnkqKUAghrCRhEaIGU7RaFJ3uutor8Z9+ypn77kfj5ESt998rdTVcIYQoK1KHRYgaLOvwYdS8PPSB1vErqqqS9P33JHz0MZ6PP4b3lCkoOvkzIYSofPKXSIgaLOHTz9AHBqL38yNl9WrStvxJ2vr1uI8di/eTT6IoSmWHKIQQgCQsQtRoWfv3Y05IIOqukQDog4Lwf/NN3EbeVcmRCSFEQZKwCFGDeT/1JLmnInHq2QO7Fi3QOjkVetz8c5f46Fwc4Z1DsdfK0DchRMWThKUMpSdeJjUhHv8GjaQpXdwW3EePLtZxsyKjAcgwWyRhEUJUCklYboGqqqiqBUXRgKqy+t03iI08iXtAIM373EFoz744uLhWdphC3LLI7s3ZlZKBl0H+ZAghKoeiqqpa2UGUheIuT10aK157kfhzZ1DNZixmMxaL9btqsdiOURQNqmqh97hJxJw6wcmwv1FVqN+uI837DiC4eSsUjXwyFUIIIa5V3Pu3fFwqhovHjhDSuh21GjdFo9Gi0WrQaLUoGi2KRkG1qKgWC67ePtRp1RaArLRHOfrXFg5s+p2Vb76Mi7cvzXv3J7R3P5w9vCr5FQkhhBC3F0lYikFVLYS0akvL/oOKfY69swttBg+n9aBhxJw8zsHNvxO2+gd2/LCUOi1bE9SsJbWahOJTpx5aqXMhhBBC3JTcKYtBVVUUTekG0SqKQkDDxgQ0bEyvhyZxfMc2ju3Yxt8rlmDKzUFvtMO/QSNqNQ4lsEko/g0akZ54mS2LFpB8KY66rdtRv10nAho1QSPVRoUQQtRQkrAUQVVVUFXrwNpbZHRwoEW/gbToNxCzKY+405FcPHaYC8cOs++3Nez8cam1q0lRcPLwpHZoS47t2Eb4r6uwc3YhuHkr7Bwd/3VNR3zrNcCvXkOcPb1kdpIQQohqSRKWolwZk1zWiYBWp7e1vLQfNgrVYiHhwjkuHj2MKTeHlncMRm+0Q7VYiD19ksg9YZw7fIDkWFOB62QkJ/HP6h8BcHB1w79BY9oMGkpQs5ZlGq8QQghRmSRhKUL+JKrynuGjaDR4B9XBO6jOddv96zfCv36jG56bnpRIbORJYk+dIGrfHn54/b8ENWtJt/sewr/Bjc8TQgghbheSsBRBVa1Tl6tyV4uTuwf123WkfruOdL33QU7t2cWO5d+xdOZ/qNu2A93uHYt3cEhlhymEEEKUmiQsRVAt5dMlVF4URaFB+87Ua9uB4zv+YseKJXzz/JM06tyd7vc/hKuPX2WHKIQQQpSYVDIrgq043G1W9E2j0dKkWy/Gv/8Z/SdN4eKxwyz6zxT+Wf0jZpOp6AsIIYQQVcjtdReuBLdDl9DNaHU6WvQdyMMfzKdl/0Fs//4blsyYRszJ45UdmhBCCFFskrAUwTbotgymNVcmg509vR56hDFvvo9Gp2PpS8+w6evPyMnMqOzQhBBCiCLd3nfhCmAbw1LKwnFVjW/d+jzwxnv0GvsIh//cxMKnH+fEru1UkyWlhBBCVFOSsBThdu8SKoxGq6XtkOGMf/8z/Oo14JcP3mL9px9gysur7NCEEEKIQt1SwvLWW2+hKArTpk2zbVuwYAG9evXCxcUFRVFITk4u1rUuXrzIgw8+iKenJ/b29jRv3pw9e/bcSnhl4modlupXFt/Fy5vhz8xk0JSnOb5jGz++MZPM1JTKDksIIYS4TqkTlt27d/P555/TokWLAtszMzMZOHAgL774YrGvlZSURNeuXdHr9fz2228cOXKE9957D3d399KGV2byZwlVpxaWaymKQtMefRj90pskXjzP9zOfITH6QmWHJYQQQhRQqoQlPT2dMWPG8MUXX1yXVEybNo0XXniBTp06Fft6b7/9NrVr12bhwoV06NCBkJAQ7rjjDurVq1ea8MrU1RaW6pmw5KvVuCkP/O/KgNyZ/+HcoQOVHZIQQghhU6qEZcqUKQwZMoR+/fqVSRBr1qyhXbt2jB49Gh8fH1q3bs0XX3xx03NycnJITU0t8FUero5hqf7Dfdx8/bj/9Tn41WvIyjdf4uCWPyo7JCGEEAIoRcKybNky9u7dy+zZs8ssiNOnT/PZZ5/RoEEDfv/9dx5//HGefPJJFi9efMNzZs+ejaurq+2rdu3aZRbPtW63Sre3ys7Ribuef4Vmvfvzx/yP2LZ0kcwgEkIIUelKVJr//PnzPPXUU2zYsAE7O7syC8JisdCuXTvefPNNAFq3bs2hQ4eYP38+48aNK/ScGTNm8PTTT9sep6amlk/SUk3qsJSEVqej3yNTcPevxdZvv8LR1Y22Q0ZUdlhCCCFqsBIlLOHh4Vy6dIk2bdrYtpnNZrZt28Ynn3xCTk4OWm3JZ9P4+/vTtGnTAtuaNGnCypUrb3iO0WjEaDSW+LlKytYlVM3HsPyboii0u/Mu0pMS2bZkEYFNmuFbt35lhyWEEKKGKlGzQd++fTl48CARERG2r3bt2jFmzBgiIiJKlawAdO3alePHC5aKP3HiBMHBwaW6XlmqaV1C/9b9/ofwDq7D2g/fJjcrs7LDEUIIUUOVKGFxdnamWbNmBb4cHR3x9PSkWbNmAMTGxhIREcGpU6cAbAlOYmKi7Tp9+/blk08+sT2ePn06u3bt4s033+TUqVMsXbqUBQsWMGXKlLJ4jbekJg26LYxWp2fIk8+SkZzMpq/nV3Y4QgghaqgyvwvPnz+f1q1bM2nSJAB69OhB69atWbNmje2YyMhIEhISbI/bt2/Pzz//zPfff0+zZs14/fXXmTt3LmPGjCnr8ErMYlutuWa2sAC4+9ei38THObJtM0e3/1nZ4QghhKiBFLWaTAFJTU3F1dWVlJQUXFxcyuy6ly+cY9F/nuC+1+ZQq1GTMrvu7eint2aRk5HB/a/PqexQhBBCVBPFvX/XzH6OEqjulW5LIrh5ay5FRWI2yZpDQgghKpYkLEWoKZVui8O/QSNMebnEnz1T2aGIMqaqKjExMaiqSlZW1tWuUCGEqCJKNK25JspPWDTVcPHDkvIJqYfRwZE9v/zEkKeek1anaiArK4vo6GhWr15doFp0z5496d27dyVGJoQQBUnCUoT8LiHk5oxOr6ffpCn8+uE7BDVrSYt+Ays7JFEKFy9e5NChQ5w8ebLA4HeAgIAAoqOjy22pCyGEKC3pEiqCrUvoFhKWbdu2MXToUAICAlAUhVWrVl33HC+//DL+/v7Y29vTr18/Tp48ed11fv31Vzp27Ii9vT3u7u6MGDGiwP4nn3yStm3bYjQaadWqVanjvZnGXXrQot9ANi/6nEtnTpfLc4jyoaoqe/bs4csvv+TgwYMEBQUxcuRIpk6dyssvv8ysWbOYPHkyoaGhnDx5ksxMqbsjhKg6JGEpwtVKt6V/qzIyMmjZsiXz5s0rdP8777zDRx99xPz58wkLC8PR0ZEBAwaQnZ1tO2blypWMHTuWhx9+mP379/P333/zwAMPXHetCRMmcO+995Y61uLoNW4SHgGBrJ0rxeRuFwcPHuTTTz9l7dq1tGvXjqeffpphw4bRokULvLy80Fzz+53/u7d79+5KjFgIIQqSLqEilEWl20GDBjFo0KDCr6+qzJ07l5kzZzJ8+HAAvvnmG3x9fVm1ahX33XcfJpOJp556ijlz5jBx4kTbuf9ezuCjjz4CID4+ngMHDpQ63qLoDUbunPYC382YxsYvP2XQ1P/IeJYq7OzZs6xcuZIGDRowcOBA6tate9N/LxcXF9q1a8e2bduoW7duuS0sKoQQJSEtLEVQy3nxw6ioKGJjY+nXr59tm6urKx07dmTnzp0A7N27l4sXL6LRaGjdujX+/v4MGjSIQ4cOlUtMxeERUIv+k6ZwdPufHNqyodLiEEXbv38/7u7uPPDAA9SrV69YyWW/fv0ICAhg+fLlZGVlVUCUQghxc5KwFKG8Fz+MjY0FwNfXt8B2X19f277Tp61jRWbNmsXMmTNZu3Yt7u7u9OrVq8CSBxWtSbdeNO9zB5u/nk9qQnylxSFuLCIigr1799K6desStYLpdDpGjx5NdnY24eHh5RihEEIUjyQsRakCix/m18T473//y6hRo2jbti0LFy5EURR++OGHSosLoN3QUZjyckmJi6nUOMT1YmNjWbNmDW3atKF79+4lPt/FxYVGjRoRHh6O2WwuhwiFEKL4JGEpQnkvfujn5wdAXFxcge1xcXG2ff7+/kDBMStGo5G6dety7ty5comrpGrq4pBVldlsZtWqVXh5eTF48OBSJ9zdu3cnKSmJXbt2lXGEQghRMnKXKUJ5V7oNCQnBz8+PTZs22balpqYSFhZG586dAWxTlY8fP247Ji8vjzNnzhAcHFwucRVXfkJXkxeHrIpOnDhBbGwsw4cPR6cr/dh6Pz8/OnfuzObNm7l06VIZRiiEECUjs4SKcHWWUOlzu/T0dE6dOmV7HBUVRUREBB4eHgQFBTFt2jTeeOMNGjRoQEhICC+99BIBAQG2OisuLi489thjvPLKK9SuXZvg4GDmzLEuQDh69GjbdU+dOkV6ejqxsbFkZWUREREBWFtmDAZDqeO/GTXDxL0hz0NUHjQul6cQpZCXV3brPfXp04dTp06xatUqJk+eXGbXFUKIkpCEpQiq5Urf/S2MYdmzZ0+BMudPP/00AOPGjWPRokU899xzZGRkMHnyZJKTk+nWrRvr16/Hzs7Ods6cOXPQ6XSMHTuWrKwsOnbsyObNm3F3d7cd88gjj7B161bb49atWwPWBKlOnTqljv9mLJkm6w/7MqHwmduiEjRq1Ag/Pz++/PJLOnfuTL9+/QrUWikJvV5P165dWbVqFZmZmTg4OJRxtEIIUTRFze/zuM0Vd3nqkorat4ef3prF5M8W4ezhVWbXrS7i9p0gb7l1/I3v023R+8jNrKrIzc1l1apVHDlyhOHDh9sS2NJIS0vjww8/pGPHjvTv378MoxRC1HTFvX/LGJYiyOKHN6ear+a7id8fQ82TVX6rCoPBwD333EPt2rVvuZCgs7MzPXr0YMeOHZw4caKMIhRCiOKThKUIV2cJyaDSQuUndN1cyIvPIuW3qEoOSFwrOzublJQU3NzcbvlaXbp0oWHDhixdupTVq1dTTRpnhRC3CUlYipCXk1PZIVRt+QmLrxHXQXVI3xFN9omkSg5K5Pvhhx/IysqyzTi7FTqdjnvvvZf+/fuzb98+26BuIYSoCJKwFCFqr3UBuBxZ5K9Q+bOoUBScOgdgbOBG4vJjmFIk0asKVFXFxcUFL6+yGX+l0Wjo2rUrLVq0YN26dRw+fLhMriuEEEWRhKUIfvUbAmC0l8GkhVGvVOFVtAqKRsHjvsYoOi2JS46immQ8S2Xr3Lkzly9fJiEhoUyve+edd9KoUSN++OEH1q5di8lkKtPrCyHEv0nCUgQHV+u0Ya2+fOqY3O7+vZq11lGP54NNyL2YTvKvpyszNAEEBgYCcObMmTK9rsFgYNSoUQwcOJB9+/bJmBYhRLmThKUI5b344e3OlrBc8/4YajvjNrQeGTtjSPvrQmWFJgB7e3tCQ0P5448/OHnyZJleW1EUOnXqxMiRIzl48CB///13mV5fCCGuJQlLEWxdHjJLqHD5pfn/9f44dfLHuVcgKb9GkREeV8iJoqKMGDGCkJAQVqxYQVJS2Q+IDg0NpXv37mzatImzZ8+W+fWFEAKk0m2RbGsJ1bDF/SwWCxf/3I8pIxvVolpbUtRrvqsqWFRyYtJwww2lkCqqLgPqYMkwkbTyBBp7HfZNPSvhlYj8SrUnT57k0qVLBaojl5XevXtz9uxZfvrpJx577DHs7e3L/DmEEDVbzboLl4KthaWUZc1vV5f2nkD5Ix393yYMO80YwywY/1Gx2wN24Qr2ezXYR2hxi3Mjz5KLvZfrdddQFAW3u+pj38STy0uPkrlfFs+rDGazmd9//x0fHx/q1atXLs+h0WgYOXIk2dnZrF27VsazCCHKnLSwFKG8V2uuqkyZV6YlD3TGrVFtFI2CotGgaDUoGsW6Lo1Wg0arQdFp0d5gRWBFo+Bxf2PivzhI4rLj6P0c0fs6VuArEWFhYcTExPDII4/c0srNRXFzc2Po0KH8+OOP1K9f/5aWAhBCiH+rWc0GpXC10m0Ne6uulNy383LFyd8TR18PHLzdsPdwwc7NGYOLIwZHe3R2xhsmK/kUnQavCaHofR1IWHgYU3J2RbwCASQnJ7N582Y6duxomzFUnpo1a0br1q1Zt24diYmJ5f58Qoiao4bdhUvu39N2awrLla4wjbZsfkU0Rh2e45uBAvFfHMSUKElLRYiMjMRkMtGnTx8Atm3bxtChQwkICEBRFFatWlXgeFVVefnll/H398fe3p5+/foVOrvo119/pWPHjtjb2+Pu7s6IESNs+wYOHMjMmTPx9PREURTb17Jly8rzpQohqjlJWIqgWiw1r3WF8pnOrXMz4j2pBZhV4j7cS/Zx+QRe3jIyMgDQarW2xy1btmTevHmFHv/OO+/w0UcfMX/+fMLCwnB0dGTAgAFkZ19NMFeuXMnYsWN5+OGH2b9/P3///TcPPPCAbb/RaARg+PDhHDhwgJiYGGJiYgokNUIIUVIyhqUIqqrWuPErANjqq5RtsqbzsMP3qTYkLj9OwqLDuA6pi1PXgBrXglVRgoKCADhx4gRNmzZl0KBBDBo0qNBjVVVl7ty5zJw5k+HDhwPwzTff4Ovry6pVq7jvvvswmUw89dRTzJkzh4kTJ9rObdq06XXX8/Dw4MSJEzRv3rwcXpkQoqapeU0HJaSqlho3QwiA/Eke5ZCsaex1eD7UFKcegaSsPU3SypNYsqW0e3k4evQoBoMBf3//Io+NiooiNjaWfv362ba5urrSsWNHdu7cCcDevXu5ePEiGo2G1q1b4+/vz6BBgzh06NB111u7di1jx46lTZs2fP311zJzSAhxS2rgnbhkVItaI7uEuGZRw/KgaBTcBoXgfk9DMvfEEfvObiy55nJ5rprs9OnTtGjRoli1V2JjYwHw9fUtsN3X19e27/Rp63ILs2bNYubMmaxduxZ3d3d69epVYJDta6+9xg8//MDkyZNp2rQpTzzxBB9//HFZvSwhRA1UA+/EJaRaamR3Rf5n4fLuDnNs44vHmCZYMk3EvbuHzAPx5fp8NU1mZmaZFnHLH4z93//+l1GjRtG2bVsWLlyIoij88MMPtuNeeuklevbsybhx46hfvz6TJ09mzpw5ZRZHUcxms7ToCFHNyBiWIlgslho9hoUKeOkOzb3Q/6ctKb+dIXHZMRSDFvvGHuX/xNXc/v37ycjIwMfHp1jH+/n5ARAXF1egCykuLo5WrVoB2LZfO2bFaDRSt25dzp07d901W7ZsyZ49e7h06RIXLlwgJyfHNij3VqmqSkJCArGxsaSnp6PX63F1dcXX15f58+eTmZlJixYtCA4OplmzZmX2vEKIyiEJSxFUtWZ2CalU7JIEem8HPMc04fKSo1z+9gjOvWrj3DMQjUFbIc9f3ezbt49ffvmFli1b0qxZs2KdExISgp+fH5s2bbIlKKmpqYSFhfH4448D0LZtW4xGI8ePH6dbt24A5OXlcebMGYKDg6+7pkajYfDgwSxfvhxHR0dbC82tUFWVM2fOsGrVKlJSUgDQ6XSYTNePg4qPj+fgwYNs2rSJpk2b4uLiQsuWLdHr9Tg4ONxyLEKIiiMJSxGs05prYgvLle8V2LqkaBU8729MyoazpP15nqxDCXiNC0XnYVdhMVQHx48fZ/Xq1bRp04YhQ4YU+P1NT0/n1KlTtsdRUVFERETg4eFBUFAQ06ZN44033qBBgwaEhITw0ksvERAQYJuS7OLiwmOPPcYrr7xC7dq1CQ4OtnX1jB49GoBffvmFuLg4OnXqhJ2dHRs2bGDHjh107tyZhQsXMmbMGFxdr1/K4WZUVSU2NpbDhw9z5MgREhMTCQoKstWUcXBwQFVV4uPjuXjxIvHx8bRt2xZPT0+Sk5PZvn0758+fJykpic2bNwPWyrxarZaWLVuSlZXFpUuXCAgIoFOnTjg6SjVmIaoaSViKYJ3WXPNaWFALL5i3bds25syZQ3h4ODExMfz8888F6muoqsorr7zCF198QXJyMl27duWzzz6jQYMGBa7z66+/8tprr3HgwAHs7Ozo2bMnq1atQtFrMHd0YeK7k9m/J4KkZ1Pw9vFhxMgRvPnmm7i4uJT7S7/dpaWlAXDHHXfY6q/k27NnD71797Y9fvrppwEYN24cixYt4rnnniMjI4PJkyeTnJxMt27dWL9+PXZ2V5PGOXPmoNPpGDt2LFlZWXTs2JHNmzfbBvbq9XrmzZvH9OnTUVWV+vXr88EHHzBixAiWLl3Kl19+yZgxY2xdUDeTk5PDtm3bOHr0KImJidjZ2dGkSRMGDRpE3bp1C7w+RVHw8fG5rgvMzc2NO++8E4CUlBT27duHs7MziYmJtkrALi4u+Pr6EhYWRlhYGOPGjaNWrVoleduFEOVMUavJyLTU1FRcXV1JSUkp05ta2M8r2PvbGh5f8F2ZXfN2cHr1Tgw7Tbg+2RjnAG/b9t9++42///6btm3bMnLkyOsSlrfffpvZs2ezePFi2yf0gwcPcuTIEdtNb+XKlUyaNIk333yTPn36YDKZOHToEPfccw8ASUlJLFu2jDahrdD9lczJw8d5efsntO3Snu+XfV+h78Pt6LfffmPv3r08/fTTVW7V5LS0NJYuXcrly5cZOXIkjo6O6HQ6tFotOp0OnU6H2WxGq9Vy8eJFli9fDkDr1q0JDQ0lJCTkuiTsVuXm5qLX61EUhYyMDJYuXUpGRgZPPvmkdc0sIUS5Ku79W1pYilBju4Ru0MJSEYXH3N3dbWMm1C4W6q1vxIn4M8z/7XtyTidjrOtWlq+0WomLi+Off/6hb9++VS5ZAXB2dmb8+PEsXry42KX6R40aVa7F5wwGg+1nR0dH+vfvz6JFizh79iwhISHl9rxCiJKRhKUIlhqasOQPui1JHZaiCo/dd9991xUei42NpVWrVsyZM6fQwaGKTkNmGzs2Ze2lc0hrsg5dloTlBsxmM7/++iuenp506tSpssO5IaPRyIQJE0hMTERVVcxmMyaTyfZdVVVSUlKoVasWAQEBFR5fUFAQ/v7+rF69mgcffBAvL68Kj0EIcT1p7yyCqqpQE5uF8/OVEgy6LcvCYwD3338/Dg4O1KpVC1cPNz6c8iYZu2NJ3xFtW5RSWFksFlatWsWFCxcYMmQIuiJW0K5sOp0OHx8ffH19CQgIICgoiJCQEBo0aEDDhg1p3759pSQrYJ3ZdM8996DVavniiy+Ij5faQEJUBTXwTlxCNbRwXHmV5i9u4TGADz74gL1797J69WoiIyP5354vcGjnS/KaSBK+OogpWVZ8BmtSvWbNGg4dOsSoUaOkG6MMuLu7M2nSJHQ6HREREZUdjhACSViKpKpqDR14d2UMSwl+Ra4tPHatuLg4276SFB7z8/OjcePGDBs2jM8//5z5C+aT3cERr4nNMCVkEffBXjL2xNb4iqYnT54kIiKCESNGEBoaWtnhVBtarZbc3NwqORZIiJqoJt6JS8Q66LYGvk35SUAJXvq1hcfy5Rce69y5M1Cw8Fi+mxUey5ffMpOTk4NdA3d8p7XFPtSTpB9PcvmbI5jTckvw4qoPi8VCREQETk5OtGzZsrLDqVZiY2PJy8ujTp06lR2KEAIZdFskax2WmtclpNrG3BZ87RVReGzdunXExcXRvn17nJycOHz4MM8++yxdu3a13Tw09jo87mlkTVp+PkXcB+G43VUfh+be1BSqqrJu3TqOHDnCqFGjKjucasfDw7o8xOXLlwkMDKzkaIQQkrAUwWKxkJedzYld28nLycGUm3Pley6m3FwsFjOqxYJqMWOxWK78bLnmZxWNTotGq0Oj0aBc+dJc8x1FU2CfoihXE4Ur321pQ/7ja7/bzldQlGuu8a/rKRrtlWOuOe5f52g0GjQ6PZnJSdjhfl3CUhGFx+zt7fniiy+YPn06OTk51K5dm5EjR/LCCy9c9+9jH+qFIdiF5J9PkbjkGFmtLuM+rB4aB/0t/9tXZaqq8vvvv7Nnzx6GDRtWrtN+aypHR0d8fX2JioqS1ishqgApHFeEsJ9XsH3ZN7bHiqJBZzSiNxrR6vVotFprsqBcm4horyYjGgXVbLauHlsgmbnyWFWvS3S40v1hm1qc/832T6VeeWz9j/U6V66rqlebR25BkGMTOvsMw2dmOwxOVb8PX1VVsiLiSVodiWLQ4DGqAXaNqucCiqqqsmnTJrZv387gwYPp0KFDZYdUba1evZq4uDgmT55c2aEIUW1J4bgy0mHEaEJ79UNnMKAzGNHqdFV+1pCqqqiqtXVHVVVrcqSq1sdXkpv8ZMmWJF05x2I2YzGbyT2ainlTErprimpVZYqi4NDaB0NdV5JWniRh4WEcO/rhOrguGmP1WUBRVVU2btzI33//zYABAyRZKWfu7u4cOXLkyiKoVfv/eyGqO0lYiqAoCk7ut9cndWuXj/aaAbMl7x7JiL9EEkklqRtXJehcjXg9HEpGWCwp606TfTIZ9xH1sWvoXtmh3bKsrCxWrVrF8ePHGTBggG0gsyg/mZmZtrL9QojKJQmLKJytW+n2+0OtKApOnfyxa+BG4o8nSfj6EA6tfXAbWve2HNtisVgIDw9n69atmEwm7rvvPho3blzZYVV7qqpy/PhxGjVqVNmhCCGQhEXcyO2br9joPO3xntyczL2XSF4TSfapJNyG1cc+1PO2mfmVkZHBypUrOX36NC1atKBPnz64ublVdlg1QlxcHElJSTRs2LCyQxFCIAmLKMrtcV+/IUVRcGzri119N5JWnSJxyVE0jjpcBtTBsa0virbq1thJSUnh22+/JTMzk7Fjx1KvXr3KDqlG2bVrF87OzvK+C1FFSMIiCmebaHSbZyxXaF2NeD7UlNwzqaTvjCb5p1Mk/3SKz31/QN/Ji8dbPo63Q9Wo4WI2mwkPD2fz5s0YjUYmTpyIp6dnZYdVo5w+fZqIiAgGDhxY5ddlEqKmqLofL0Uly68cV7lRlCVFUTCGuOL5QBMu1ckA4NG40UR9d5B6Xeth72mPoijMWjCLhKyEAucePXqUYcOG4erqiqOjI+3bty+wlEBsbCxjx47Fz88PR0dH2rRpw8qVK0sUX25uLhERESxYsIB169bRtGlTJk+eLMlKBVJVld9++43vvvuOkJAQmYUlRBUiHx1E4arBGJabce9flxO/R+Ab7UyIGkT/Tv1RRius/O9KFh5ayMoVK2np3ZJRDUYRYgqhb7e+TJw4kVdffRUXFxcOHz5coBjeQw89RHJyMmvWrMHLy4ulS5dyzz33sGfPHlq3bn3DOHJycjhz5gw7d+7k7NmzqKpKSEgIkyZNolatWhXxVohrREREEBYWRu/evencuXMNXUdMiKpJCseJQmX8E0vSTycJfKt7ZYdSriJeXkt8SAb9H74XsLbCLFq2CJ8OPqw8uZJ/Yv7h3KfnsDPaMf3d6QyvPxw3oxsedh4YtFdr1Dg5OfHZZ58xduxY2zZPT0/efvttHnnkEds2s9laEfncuXPs37+fQ4cOYbFYcHNzo2nTprRv395W8VdULFVV+eyzz/Dw8OC+++6r7HCEqDGkcJy4JSpqtW1dyXfyu6N45bpy9Eg2B08dp3l96/RVV6Mrg0IGMShkELHpsdR5og7GAUbemPgG/z37XwzeBnzv9OXE+yfQa63TpLt06cLy5csZMmQIbm5urFixguzsbDxCPVhydAmpOansu7iPgN0BtufXarV07NiR9u3b29atEZUnIyODS5cu0b59+8oORQhRCElYROFUbsuEJS8jl0v7LpGXa0HRadAZtWiNWrQGLTp7HTo76/eYzeexP5TAOZOZ6FwNCe+e41f/PQDsCI+wLdZIOuRk5pD+ezrPzHyG5p2a8+Y3b7Lv4300cmjE6w+9jl6j565X72LeM/Pw9PRE0SpoDBoCpwTyyolXMGgMuBndUJNVArAmLI8++ii+vr7S5VCFODo64unpSXR0dGWHIoQohCQsonDq7ZOxZCZkEb35HDnHknDMyEWnKLZfbBUwXfnKueYcA5Bq0NLpza60ys3l+5W/kXHU+npjjqXYjrNcWddp+PDhvDrjVQCG9hhK4+ONSdySyFuN3wIg+ttocuNy6f5ad0ICQkjYk8DWz7fy0bqPGNh5IAatgTX/rGFv9F5C+4Ti7+9fru9JTZWWlsbevXtp1aoVrq6uJTpXURTq16/PiRMnyik6IcStkIRFFK4S8hWzyULGxXQyYzPIScgiNyUXpwZu+LXzLVAa3WK2EBcWS1J4HFzKxCnXjJ2ikKfVkF3PHY/2PhidjKgmC+ZcM+YcE6YcM5YcM+Zc6zado56GPWuh0WhwsLNj4pi7AJjxvzFYNBbbc3l5eaHT6WjatKltm1Fr5J7u97B9+3Z+uvsnwg+HM2TTEA4dOkRoaKj1oInQ72Q/1n23jmHdhlnjvpL8tGnQprzfyhrFZDKRnZ3NxYsX+f777wHYsmUL06ZNK3GRPYPBYPt3EkJULZKwiMKpUFELCVksFs79doa8vy6Svy60FrAHzAfiObrqFIZ2fniEehK7/gz66HTsAaMKOXZaspt74987kMBazmUSj6q5Og7dYDDQvn17jh8/XuCYEydOEBwcjK+jL7XtawNc172j1WoL3Pzyx7fLujRlJyMjgzlz5hS6b+7cubRo0YK77rqrwHuuqirZ2dlkZ2ejqioGg8H2OD4+HgcHh4oKXwhRApKwiEJZV6ct/+eJ3n6R5N/P4JJnIdOoRd/JH3s/Rxz8HLB3s+PilvMou2KwC4shMywGR1Ul3cMe+07+1OkagFZ362NALsREM+e5JWjzrLN+klLjiIiIwMPDg6CgIJ599lnuvfdeevToQe/evVm/fj2//PILf/75JwCNGzemfv36PProo7z77rt4enqyatUqNmzYwNq1a23PY8GavGiV6rN6dGWKi4vjs88+K3Sfg4MDWVlZHDhwgEuXLqHVarl48SI6nQ6z2czNJkc2a9asvEIWQtwCSVhE4UrYJZSbnsvJ+QfQXc7GogHVxwHHJp74dvTDztVoO85isZB0LInL+y5hOpGES44ZrUbB1COQxgODr2ulCB4cgjqoDgm744jfGY1v/2CCm5ZtIbVNW7bw0XfP2R6vX7eC9etWMG7cOBYtWsRdd93F/PnzmT17Nk8++SSNGjVi5cqVdOvWDQC9Xs9niz7jyf97kj79+pCbk4uHjwf3PX4fMcSwascq/Dz9SEmzjo3RaiRhuRWqqrJnzx42b96Mp6cngYGBNG7c2LZIYf7vUGpqKtu2bcNkMmEymbh48SImk4khQ4bw22+/Xdf14+/vz8iRI2WtJiGqKElYRKFyIpNRcwv+QbdYLCQcuEz66WRy4rOwZOShc79SPO1EEo4WCxleDpBjwi46A21MBpc2nSUPBbMGzBoFo0nFoICdqpKh05Db0Z8GQ+uiuUlLiaIoeHfww7uDX7m81osH4ZNHNwHg2CuNJk2D6diiVYFjJkyYwIQJE254jfMZ57ln2D1kO2eDApY8C5o8DWf/Oct5zhc41sGu+nc5ZGdnYzQar+uKKYvusO3bt7Np0yZatWpF7969bzi41sXFhTvvvNP2+NChQwC0b9+eli1bcvDgQerWrcuZM2dYvXo1MTEx6PV69Prbb0VvIWoCSVhEofIuZwNwdPFh1CwzanI2huQc7LHOsFFUlTyNgjHOWuI+S6fB8YEm1GluXY8nvyUlMSIeU0oOlmwT5JjJdtSja+KBT/uCLS+VySXJ1/Zzxp/ORGyKoOMXrUp0jfwb8X+f+C/O9lfH0mTlZXEu4RzRCdHEJcWh1+rxcK5+NVfMZjPr16/n1KlTJCUl2bYPHTqUpk2bsmbNGo4ePWpdHsFopGXLljRq1IicnBxOnjxJdnY29vb2dO7cGS8vrxs+z4ULF9i8eTPdu3enb9++JYoxJCSEqKgoLly4QGBgIG3btgXA1dWV1atXA9Zk6NokRwhRdUjCIgqVHOCIU1wGzkcTyVMhR6uQ62mPXWsfvNv5YOdmbVmxmCyguX7AqUajwbOpJ55l3H1THpR/Lal1990BNzjyei989gLaeC0aVYMWrbXg3jXs9fY08m9EI/9GZRJrVWM2m/nnn3/466+/yMzMJCgoiCZNmrBjxw4AfvnlFzZv3ozFYuGOO+5Ar9eTnJxMeHg4YWFhAHh7e+Pi4sKFCxfYt28fw4YNo1WrVtc91+XLl1m5ciX+/v706tWrxLEOHjyYefPmsXr1aqZMmWLbnpaWBkCdOnUIDw+nQ4cO+Pj4lPzNEEKUq1tKWN566y1mzJjBU089xdy5cwFYsGABS5cuZe/evaSlpZGUlFRkn/CsWbN49dVXC2xr1KgRx44du5XwxC3IcrfnbxM88t7NS/PfrCvndpEbGovlpDOqYobaGXgOGAPAyeiTxKbE0jy4OW4OboWea0oxoXHU4B3ijburOy72NWdZiOjoaH755RdiYmJo06YNdevWpWHDhhgMBu644w6io6PZtWuXreXk2r8Dffv2JSkpCVVVrcX2FIW8vDzWrl3L2rVrCQkJwdXVldzcXBRF4fjx46xZswZnZ2fuvvtutNqSjwNydHQEID4+npSUFFtXUmpqKgD9+/dn+fLlbN++nZEjR976GySEKFOlTlh2797N559/TosWLQpsz8zMZODAgQwcOJAZM2YU+3qhoaFs3LjxamCypHulMpssaLW3fzJSHNP/7wEA3npuOforL3nBmgVE77VWPN0QsIHXJr9W6LmKquDq7cqTI5+skFjLSv6aRqUdr7F7927WrVuHj48PjzzyCIGBgdcdExAQcMMbv0ajuW4Var1ez6BBgzh58iTz5s3DaDTaWj/AOntn6NChGI0l70pMSkpi4cKFtsfz5s3jiSeewM3NjejoaLRaLd7e3nTp0oXff/+dPn36yOBbIaqYUmUF6enpjBkzhi+++II33nijwL5p06YB2KZ8FjsQnQ4/v/IZVClKLifTRG62qbLDqHB5sTo27NjBmbNnMGAgQ5eBJlHDsq3LuK/n9QviKapyuxQEBqwfKLZs2cLhw4fJysrC19eXwMBAateuTaNGjQqsQH0j8fHx/Prrr7Rv356BAweWqrXjRuzs7Bg9ejR79+7Fzc0NT09PLl68iLOzM927dy/VoN3k5GQWLVqETqdj+vTpHD16lPXr15OVlYWbmxtpaWmoqkpmZibBwcGoqsrBgwfp3r16L/wpxO2mVAnLlClTGDJkCP369bsuYSmtkydPEhAQgJ2dHZ07d2b27NkEBQXd8PicnBxycq4WW89v1hVlY/+m80UfVM3oA0zoTngR/nsUeEKuRy5+Pn4kHU/i2JZjLFeWM7j94AKDahUUFE3VzlhUVeXIkSOcOXOG06dPk5aWRrt27XB3dyc6OpozZ86wZ88ePDw8eOCBB2466BVg37592NvbM2DAgDJNVvKFhIQQEhJie1zYeJbiyMrKYuvWrRw6dAidTse4ceNwdnZmx44dhIZeXR6ha9eu7Nq1i7///tu2Umzr1q1v+XUIIcpWiROWZcuWsXfvXnbv3l1mQXTs2JFFixbRqFEjYmJiePXVV+nevTuHDh3C2bnw6qWzZ8++btyLKDshLb2I2p9Q2WFUqP9MG8Pb//sOcq4mIP+57z98vu5zYv6J4ejmo+zduRe/en5otVq0Wi32ufZVuoUlNzeXNWvWcOjQIby8vPDx8WH06NHXtWZu2rSJv/76i08++YR7772XJk2aFHo9s9nMgQMHaN68eZXutrVYLPz4449cuHCBZs2a0b17d1xdXYmLiyM1NdU2QwjA3t6evn378vvvv9tacOzt7W90aSFEJSnRIIXz58/z1FNPsWTJkmI1HRfXoEGDGD16NC1atGDAgAGsW7eO5ORkVqxYccNzZsyYQUpKiu3r/Pma1yJQnjwDnXB0K920423btjF06FACAgJQFIVVq1YV2K+qKi+//DL+/v7Y29vTr18/Tp48WeCYOnXqoChKga+33nqrwDErVqygVatWODg4EBwcfMMS7SVhspjI5DSGRIMtEXl08KM89cxTZDlkoc3VEn80nksHLxG7LxYAL8+bt0hUFpPJxNKlSzl+/DijR49m6tSp3HvvvYV2vbq7u9t+Xr58OVu2bMFsNl933NGjR0lPTy91q0dFCQ8PJzIyktGjRzN06FDbeJTz58+jKAq1atUqcHznzp0ZOnSorQLupUuXKjpkIUQRSvQRKTw8nEuXLtGmzdXF28xmM9u2beOTTz4hJyenTJqI3dzcaNiwIadOnbrhMUajsVSD70TxaLUKFsuNy5ffTEZGBi1btmTChAmFDrp85513+Oijj1i8eDEhISG89NJLDBgwgCNHjhRIhF977TUmTZpke3xta9tvv/3GmDFj+Pjjj7njjjs4evQokyZNwt7enqlTp5YqboC03ATstNYbtZf/1UTE3cmdt597u9TXrWiqqrJx40bOnTvH+PHjb9q9Clw3wHTr1q1kZWUxePDgAtt37tyJn59flV9t+sCBA7YlE651/vx5/Pz8Cv3b0bZtW06dOsXRo0eJjIys8q9RiJqmRAlL3759OXjwYIFtDz/8MI0bN+b5558vs/7s9PR0IiMjGTt2bJlcT5ScolFQzaVLWAYNGsSgQYMK3aeqKnPnzmXmzJkMHz4cgG+++QZfX19WrVrFffddHdjq7Ox8w4HY3377LSNGjOCxxx4DoG7dusyYMYO3336bKVOmlLqiqv7KSs1jHxtLPb96pbpGZbJYLOzatYvw8HAuX77MHXfcUWSyAhTa9frPP//QvHlzate2Lu6YlJTExYsX6d+/f5VewFFVVS5dumRbOuFa58+fvy6JuVaDBg1sCUth5wshKk+JuoScnZ1p1qxZgS9HR0c8PT1tC4bFxsYSERFhax05ePAgERERJCYm2q7Tt29fPvnkE9vjZ555hq1bt3LmzBl27NjBXXfdhVar5f777y+L1yhKQaPRYDFbij6whKKiooiNjaVfv362ba6urnTs2JGdO3cWOPatt97C09OT1q1bM2fOHEymq7OWcnJyruuWtLe358KFC5w9e7bU8fm6Wiv1hviEFHFk1ZOWlsbq1av5448/qFWrFuPGjaNLly7FOvdGXbwrVqwgJcW6BlJkZCRAgQGxVVFmZiY5OTnXtRqZzWaSkpLw9va+4bkeHtYqxFFRUTddIPHfVLOFlPVRXF56tETnCSGKr8xHzc2fP7/AYNgePXoAsHDhQsaPHw9Y//AlJFwd0HnhwgXuv/9+Ll++jLe3N926dWPXrl03/cMiypfmFrqEbiY21jruw9fXt8B2X19f2z6AJ598kjZt2uDh4cGOHTuYMWMGMTExvP/++wAMGDCA6dOnM378eHr37s2pU6d47733AIiJiaFOnTqlis/ZzonkFPvrKvdWVWazmf379xMeHs7FixfRarWMHDnyuvpIRXFwuLq+kV6vJy8vjy5dunDo0CG+//57Jk6caEtYrh3vUhXZ2dnh4OBATEwMzZs3B6zdlL/99huKothajApzbd2X1NTUG65TdC3VZCHh60PknLYmdrld0zAG15wCgkJUlFtOWP5db2XWrFnMmjXrpuecOXOmwONly5bdahiijJVXwlJcTz/9tO3nFi1aYDAYePTRR5k9ezZGo5FJkyYRGRnJnXfeSV5eHi4uLjz11FPMmjXrlpINjUZzXXn9qiYjI4Po6Giio6PZt28fycnJNGzYkBEjRtCwYcMCyUdxabVaa6uaxYKrqysJCQmkp6fzwAMP8OWXX7J8+XJiY2MJDQ2t8jNotFotDRo0sLWSHDt2jHXr1pGVlcWIESNuWu/p2pbgxMTEYiUsaVsvkHMmFa9JzUlacYLMvXGSsAhRDqruvERRqRSNgqWUY1huJv9mERcXV2BQY1xc3E1nnnTs2BGTycSZM2do1KgRiqLw9ttv8+abbxIbG4u3tzebNllXXK5bt26pYsvNMmHOVYFb6wqzWCykpaVhNptxcXGxTf9VVZWkpCTS09Mxm822mVD50tLSOHPmDNnZ2Xh6epKdnc3p06cJCAigUaNGXLhwge3bt9tmxNnZ2VGvXj3uu+++Mim66OPjQ2xsLC4uLiQkJHDkyBFGjhzJwIEDWbt2LUCBrryqLCAggP379/Puu++SkZFBgwYNuPPOO4tMQJKTk/H19SUuLs7WFXYjqslC2vaLpG44i2Mnf+zqueHQxof0nTG43VkPRX97tNIJcbuQhEUUSqNVQAXVopZpYbSQkBD8/PzYtGmTLUFJTU0lLCyMxx9//IbnRUREoNForluUTqvV2qaofv/993Tu3LlEXYkWi8qZ/Qkc2naBC8eSyHBIx+yUx/Lly20Jh4eHBx4eHnh6euLp6WlrwVFVlZSUFM6ePcu5c+c4d+4cqamp5Obm2sYxKIqCm5sber2erKysAl0OtWrVomnTpmg0GqKjozl8+DAWiwVFUWznu7q6smfPngLn3HXXXQQGBuLh4VGmg1+dnJyAqzOGTCYT2dnZtG3blpiYmGJ3kVQFbdq0sRWXbNCgAcHBwcV6r7KzszEajWi1WjIzM296bMzsf7Bk5KHzccC5l3VpAoe2vqRtOU9GeCxOnYq/iKYQomiSsIhCabTWP+4Wi4q2hAlLenp6gSnpUVFRRERE4OHhQVBQENOmTeONN96gQYMGtmnNAQEBjBgxArBOnQ0LC6N37944Ozuzc+dOpk+fzoMPPmgbP5GQkMCPP/5Ir169yM7OZuHChfzwww9s3bq12HFazBbWLzhE1P4EfENc6PlAIzJzAzhy2kBOTg46nY7z58+zf/9+8vLyAOvA3qCgILRaLRcuXLBVWPby8iI4OBgPDw+MRiMuLi5otVqSkpJITEzEbDaj1WqpU6cOLi4uZGRk8Ndff/Hnn3+iqiru7u7069ePli1bYm9vT2JiIjqdDjc3Ny5fvsyFCxfw9/fH29u73Gbo5Ccs1w4ajY2NpU6dOgwdOrRcnrO86PV62/i5knB2dubo0aNotVrq1bv5LDGnzv6kbjyH7/+1QtFbZ0jqvexxaOtL6h9ncWjhjcahdGs1CSGuJwmLKFT+TVEtxTiWPXv20Lt3b9vj/PEo48aNY9GiRTz33HNkZGQwefJkkpOT6datG+vXr7fNVDEajSxbtoxZs2aRk5NDSEgI06dPLzCuBWDx4sU888wzqKpK586d+fPPP+nQoUOxYlRVla3LTnD24GUGP96ckJZXW2Xa92183bHp6elcunTJ1pKiqirNmjUjKCiI2rVr21YCLomb3RCvLY+f37JT3vKnNmdkZNC0aVOOHDlCXFxcqQcw3446duzIpUuX6N2793UDw/9NH2h9v8yZJnSuV0s6uA6sQ9ahBFI2nMV9+I2nUAshSkZRq8kcvPzm6pSUFNt6IKL0ju2KYdOiozz2cS+01bAv/sCWC/y1/AR9HmpMky7SdA8QFhbGb7/9hp2dHePHj+fgwYN06NDhtukGqmh5lzKJez8cr0eaYVe/4MyptG0XSPktCp8n22DwL3kyK0RNUtz7d/W7E4mykZ/GVsPfEHOehX/Wnia0e4AkK9fIr6+SnZ2Nn58f/fv3l2TlJnRe9mhdjaRtu4hqKjhQ26lLADpve5J/PlmqVkohxPWq4e1IlIXq0e5WuLOHL5OTYaJFnxvX46iJ8gc03y41aCqbolFwH1mfnFPJxM7ZzeUlR0kPi0FVVRSdBve7GpB7Lo2MsJjKDlWIakH+MolCKfm/GWVf7LbSHd52Ea/aTnhIU32hLBbrP7rFbCYyPAxLIYsgCiu7Rh74TmuDXRNPzOl5JP98ikvzIjBdzsIY4opjBz9S1p/BnJJT2aEKcduThEUUKn/QraWaNbXERaVy7kgibQfWqexQqiQ/DzeaBFmniZ89GMGqd17nwMb1lRxV1ab3ccB9RH18Hm2B14RmmBOzSVx+HNWs4jooBEWvIfm3qMoOU4jbniQsolAaTelnCVVlF44norfTUre1LPtQmIy/N3Lh99UA+NSxFuDb+9uaygzptmLX0B3PcaHknksjbcs5NPY6XAeGkBURT9aRy5UdnhC3NUlYRKHyi8VVswYW4qJS8Ql2sSVkonCqquLoZp35khRz8YbHRZ84xsEtf1RUWLcFvZ+1qzF14zlUi4pDWx/sGnuQ9NNJzBl5lRydELcvSVhEofLHsFSnFhZVVYk+mUxAfZn5UpTcrKwCj82mwm+0e9b+xB/zPyIyPKwiwqpSZs+eTfv27XF2dsbHx4cRI0Zw/PhxFL0GYwM3AHq07YJGo8H74WbUeqkzOicDjz32WIHrPPnkk7Rt2xaj0Vjo8hRnzpxBUZTrvnbt2lUBr1KIqkMSFlGoWykcV1WdjognJ9OEf323yg6lyvIIsJaYz0xJYvuyb23bD2/dXOjxnUbeB8Cqd14nLye7/AOsQrZu3cqUKVPYtWsXGzZsIC8vjzvuuIPMrEy8JzbHsZM/pqQcHnl4IjExMURuOEj4lJ+Z9dBz111rwoQJ3HvvvTd9vo0bNxITE2P7atu2bXm9NCGqJKl0KwqV32VSmSs2l6XE6Aw2LTpKvdbeBDZ2L/qEGsozMIjE6Avs+eVnDmxaj4u3L6nxcWxY8DH12nawdRPls5hMtp//Wf0jXe95sKJDrjTr1xccjLxo0SJ8fHwIDw+nR48euPQLAlVFl2zBz88P1deXxFgNORvjMDcPROtsAOCjjz4CID4+ngMHDtzw+Tw9PctkkUshblfSwiIKZRvDUg2mNVvMFtZ/cQhnTzv6jGtSbmvxVAeetYMByE63LtI44rmX6P7AeABWzXkdi9mMqqoknD9LRnISG7/6FEd3D5r3HcDuNStJjoutrNArXf7qzh4eHgBonQxonQ2s+P1nvLy8aN68Oe/sW0SWKYfEH06UuPVy2LBh+Pj40K1bN9askYHQouaRFhZRKNsYlmow6vbojhiSYjK458X2GOzkV/5mvK4kLO4B1qnNl6Ii6TD8bnR6PVu++ZIPHhhe4HijoyP3vvIWbr7+nInYy5/ffMGIZ1+q8LjLyrZt25gzZw7h4eHExMTw888/2xblBOvCni+88AKrVq3i8uXLhISE8OSTTzJ58mSmTZtG165dadasme34++6+F7cjKo3HduJ46hmef/55jjU9yry850jbegGX3kUXL3RycuK9996ja9euaDQaVq5cyYgRI1i1ahXDhg0rj7dBiCpJ/nqLQlWXMSymPDO710bRoL0v3kHOlR1Olefo5gZA4sULOLi6kRp/CYA2g4dTq3EoO35YQlLMRZJiomnavTcdRtyDZ6D1ptvroYn88sFbnN67m7pt2lfWS7glGRkZtGzZkgkTJjBy5Mjr9j/99NNs3ryZ7777jjp16vDHH3/wxBNPsHr1ao4ePcr27dsLHP/Ei08R+9Y/2Od60W5MV/z9/enbty+v3v8M/HEGYz1XjEE3X/vMy8urwMKf7du3Jzo6mjlz5kjCImoUSVhEoZRqMoYlPTGHjJRcGna4+cq7wsrR3dqdEX3iKJkpyVw4ehC4HwDfuvW56/lXbnhug45dCW7Rmk1fzyc1/hIZKckYHRxIu5yAZ63atOg3sCJewi0ZNGgQgwYNuuH+HTt2MG7cOHr16gXA5MmTmTlzJn///Tf79+8nMDCwwPEagxbnPkGk/Hoa556BdOzYEYBY3yz8M/1I/P4YPlNaoXUylCjOjh07smHDhpK9OCFuczKGRRRKU02mNed3bekM2soN5Dbh5mMd1JmRnATAuUM3HgT6b4qi0OfhR0mNj2PT15+x/49f2fnjUvauW82GLz7hwtFD5RJzRerSpQtr1qzh4sWLWCwWRowYQUJCAvPnz7ctHvlvTh39QFHIPpFEREQEAAGBAXg+0Bg1z0LiihMl7nqNiIjA39//Vl+OELcVaWERhbJ1Cd3e+Ypt0LCs51c8ikZDrcZNuXjsCABuviW7KXoEBDLmf++TcP4szXr3B6xrEi3579Ps/PF77p75xm076PlYbCp5HcbDmXgCAwNRFAVVVZkxYwZ9+vQhNtY64NjV1RV7e3siIyNZunQpgwcPRnVIZfPiFby68WN69OhBixYtAHAf3ZA97/+Oknee2NhYsrKybElN06ZNMRgMLF68GIPBQOvWrQH46aef+Prrr/nyyy8r420QotJIwiIKpVST0vy2T6636U2yMgx/ZiafPvIAAMlxJV9p2K9+Q/zqN7Q91mi1dB51P6vffYMlL04nsEkoDTt1I6BhkzKLubwkZuSw91wSl1JzeOy7cFLCfiL9wG5mfbKYWVPHAdYCcrNnz7ads3DhQsaPH4/BYGDjxo3MnTuXjLQM/J28GHbHnby+4B3bsfaNPJix60P+XnC18F5+YhIVFUWdOnUAeP311zl79iw6nY7GjRuzfPly7r777gp4B4SoOuRzpyjU1dL8t3nCcqWF5Xb9VF8Z7J1dGPXf122PczIzyM3OuskZRavfvhPDn5mJi7cP+9av5YfXZ5KeWPK1dW5UXfba/S4uLtdVhX3ssceIj49n69atdO3atdD9+fbv38/991vH7Uwc+wBtQ3wY1KIWFz55iNRti2g2ciorzxoYNfpeGjRoAEBQUBCqqqKqKuPHjwegdu3abN26lcuXL5Odm83O/65i1r3/wcWl4CDbv/btJH7RIS68soPcSxm26+QnK+PGjePIkSNkZGSQkpJCWFiYJCuiRpKERRRKU03qsOQnXJKvlEydFq1x8vQC4JOH7+XjcaPZvOjzW7pm/fadGPb0izzx5VJ0RiM7flxa4mvcqLpsRkaGbX9AQACjRo1i48aN9O3bl1q1ajF+/HjmzZvHli1byMzMJDQ0lDfffJO7776bpk2b8s47V1s9wsPD8fa2Lo6psXfBr/NwNDodd4++G4vFwuQe9UlMyyQ+z8jMmTPx9PQsVuyKTgOFrGGlaBQ87mmE1lnP5cVHZL0hIW5AEhZRqPzBqrf7LCFbwiKLHZZY+uWEAo81mrIZuGx0cKTTXfdwaPMGYiNPlujc9evXM378eEJDQ2nZsiWLFi3i3LlzhIeH2/b7+fkRGBhI3759+f7777l48SK//fYbzs7Wae1arZZ+/foxY8YMQkNDSUxMpG/fvjg7O+Po6sETs+by7ZFcAJya96Nx9zvx9nBn+aIFADzx0Gguzp+I0ZyBxWIhMTGRevXqFbkmkCXHzOqw9bRq1QoHBweCg4OZM2cOABp7HZ7jQjGn5ZL4/bHbvitWiPIgY1hEofK7UM4cTCAxOh2LWUVVrWNarD9f/X51G9bvFhWLxfr92p+t37nJPhWLhSL3WSwqan4M1x5jVrFcidH6swpX/u5rdZKbl5TRwZHcrCyGPPUcwc1bYefkVGbXbtFvIH9+8yUbFnzC2Lc/LPV1/l1dNt+SJUv47rvvcHe3LiUQHx9P7dq1SUtLw87OzrZfo9GQnJxMp36DiWkxnqzo4ySu/5ic8wcBSA37kT/DfgSsBdx+/fVXnn/tXf7ZuZ0Nv63h7IlD1K1bl+bNm6OqKhMmTCAsLKzQEvsb929j0vIX+PiTj7njjjs4evQokyZNwt7enqlTp6L3ssfjgcZcXnSY1D/O4Dqw8FlHQtRUkrCIQtk7G9DpNez59Yxtm6JRUDTW7iJFo9i+X/35ZvsUNBr+9VhB0VrHEOj0mqvHaBU0ypV9mqs/275rKOTahcehaBSM9jo8Axwr7828DR3euomczAzueuEV6rYu+yJweqMdAQ2boFpK3+dosVgKrS77wAMPEBwcjJ+fH+PHj0ev17NlyxbatWuHi4sLY8eOpU6dOgQEBDBlyhT+/vtv9uwORzdiJM7edXBo0IkLH48BjRa32o14YtLDvDnzWTQaDbNmzWLn5s0M/Xkvu9003OXvydoJ97MzOYMPP5xLZzenQtcEUs0qK/et586eA23jZerWrcuMGTN4++23mTJlCoqiYN/IA5cBdUhdfwatqxGnzgGlfn+EqG4kYRGFcnAx8MjcHmDhSlIhA1drkog/fsUzMKhckpV8rQbeybqP5rB54ef0HDsRra5kf46mTJnCoUOHrqsuO3nyZAAef/xxkpKSeOGFF3j99de5ePEiTZs2ZdSoUZjNZhRFwWAw4OTqxoXj+wlIikHv7o+LxtodhMWMvt3dvPPmGwTXqUNKcjJbtmyhYcOG0LYH6XY63tv5F6aTxyB8D30jI1k77yNSTGYALuea6NKzJyd27bga3FEYeqc706f5oKJy4aTChQsXaN68OSdPnqRJkyZERERgScsleU0kWlcj9k09+f3333nllVc4fPgwdnZ29OjRg/fee882MFeImkDaycUNabUatHqNtbVCkpUaQVVVzkSEE3f6FKG9+pXrczXu0oOeYyeyb/0vrJ7zeolmpE2dOpW1a9eyZcuW66rL/nt//gDaEydOUKdOHVasWMHrr7/OV199hclkwt7ROrZlsG8aLw9pTNTaT/EPqIVWqyV70zwcWg5g1MNTWLx4MQDB3fpxesMvZP/8AyMmTMKxUVO6DhmKajbR/447WBAVzfnsXO7fH0lUVg72Q0YS/MPPTJ7sgdGocEe7ngTqnsASdy/LVp0F4I7+/bn33ntt8bsOqYt9U08Svz/G8b8PMnz4cPr06UNERAS///47CQkJhS4dIER1Ji0sQggAzh8+wIrXXgQgqFlLWg+4s1yf76233uKnn37iyKFDKKs30GLZShauWEmjRo1sx/Tq1YutW7cWOC80NJSkpCT+/PNPUlNTuf/++9m+fTsJCQnUqVMHLy8vTp8+zZ9//omvry/r168H4IcffmDZsmV4e3vTvHlzOnfuTJ06dTh/4QIAsTl6dn03B/PlczQeej8x386lVqvuZHV8iAce7sIjGzYDsK/XAFxCW5H0zKO8NWoo8etW0SqoFos/+Yj6tQJolZdJuNlChtmCmyaPDKMdG9vrOePuSkqKmefe/p3pb6zFxcWFifffy7uffkO3JkYORNe1dSUpGgWP+xoR/8VBtn78C2azmTfeeAPNlQqIzzzzDMOHDycvLw+9Xl+u/05CVBXSwiJEDWexmDm2Y5stWQls0oy7//s6OkPJ1rcpqfwpymG7dzP7iYdxzzpO/y6tyEiKL3DcpEmTiImJISYmhnHjxnH+/HmWLl2Ks7MzmzdvxtHRka+++orDhw/j7u7O9u3bady4MXv37uXDDz9k27Zt+Pr6MmHCBMaMGYO7uzubNm3i1KlTxMTEcP7cObyD6vPnmuWsXfsLDz37BttWLsTd3R1TwlmyovZx7+wvOfTWSxjaduK9Dh1YO3IoAL///jvp6enEx8dzeM9uAFp6udPY0Y5HPaLJsajkblpLp7YP8eiERLydBnDp0iXOnj1LbGwsnbv2BKBunbrXvT+KXovnQ01pFdIUjarw1fwvMZvNpKSk8O2339KvXz9JVkSNIi0sQtRAqqoSfeIYsadOELlnF+ePHLTtu+flN1HKeS2DC4uf5Iuhbmg94lEu/MnIzn7cp7XD5910wl/rSY8ZP4FPYwAcHBzw87OucZTfLZO/+GC+bt260adPH3bu3AnA5s2b2bx5s23/sGHD8PHxISUlhYwM63TkJUuW2PbHnzsFnOKBWR/hlBqFOTOFpExISkqCQ/u4BCh29kzasotxjf35+++/Aes4GrDWblm6dClGoxEfHx8A/ndRh9JnKHeGaHit1z0cOHCA559/nouJ4/jpp58A+Pabz2na1I4mne9m1Y6PrnufkrKTCHqoFUvj5vLYCzN4/MknMJvNdO7cmXXr1t3iv4IQtxdJWISoYbIz0lk+6wUSzp0BrNOXm/boQ0DDxrToN6jcxytlxkYSGGVNPIj/zbb9VI71u4eDFhb0gsHWYm75U5D9/Px44YUXeOmll3BwcChwTVNGEhuXfcprr73Gjh07sLe35/777+fw4cMA3HvvvZw7d46oqCjmz5/P+PHjeeONN3jkkUdwbjOEjCNbqX/PCwzo3p6TyRA4pQmD29bl84e72NYESmjZgZ/PXqTN+ZO89Owz9OjRw9Zd1fXeIURs3sVDb0xn3/YIUjPSSDkVy9M9g3hh0MMYDAb8/f3Zs2cPc+fO5ZdffmHjxo38tiWcT2a3Q8VEZuI58jKTOL71HXKyY8gxxZKTF0v2ycb85/dfuTt0IPfcORJNVy9emfUKd999Nxs2bJDxZaLGkIRFiBrm5D87SDh/llEzXsXV1w8HVzeMDhU37Tsn+hgOQGzX93Fp0Qc1J4u87AymPv4MXbuaafbKH7D+eVjzfzzQqBnBT35EQINmthaK48eP21ooADi+Ht339zIQSKg/j9dee41ff/2VXr16kZiYSExMNCGBfvTr24eEy5cxmcz85z//4Y477uD06dOk77O2VJz89iVGffuS7bIt538BdLGtCXRg7lyS09J5zMcXY7c+vPP+24B1gO8/W3aj8fJj/mNXz2fyfbwCPBQ1wDabZ8cO64yh0aNH061bNxbOeRCfZn/x9+7OxKYkkmPJJDr7W/QmTwyqDzl2aXwXtgEXiz1TH5+M61ENTmkBfPvttwQFBREWFkanTp3K7x9LiCpEEhYhaohzhw4QuWcXh7duok7LNtRp1bZS4siOsVa3dQhugYOvtTja448/zrHIs9YpygYHGPYxhPRk8q//gcNPgd04mvcbj//ixfTt14/IyEjq1asHh3+GH8YDcOiSmWlzxvNcDxc67XwE045cHsaEnjyU9+ayfbSF9FwDay+48PYn73M+8hiNmrfhrv9+xmFzAMdnDwOg61ubuat1LZ4YYB38m78m0M9xSTx+5KztdWgdHJk6dSorf1qJ63tf8F5HJ0bV6cyBy6fYnxxDSl4ezzYbhPZKhWAvLy/ef/99unXrxj///EOLFi3ITLjAxUM/YOdQCz+XDTja76JX/wO2yszf/dmfS+pZ8vSuOB1RSffOg7+jycq0A6y1aISoKSRhEaKaU1WVPz7/mENb/gCsa/oMfOLpSovHuXk/csJeJ/WnZ3B5YattCvK2bdsKTlFufjc06A9hn8Ouz+CfBXTUWKcgn3qlBfXq68CjHgR2YEfQEwy7+z7u7VaPSSPbcVlvD3p7FL0D6B1QjA7oDI7UP/E9M3wPYM7Q8e1ff/Dpl4v5MSKOvb9H0nDmbxi1GtJyTOSZr08Esq8kBy46Df8X5MuXM55l2fffM3PB/3hb64h/rp70xFRauzWgi38LIiMjefN/bzJ48GA8PT05cOAA06dPp0ePHrRo0QIAB69AlMChXE5PJzVvM9m5uew/sB+Apk2bomj0tOnoxPqfT/PKoU+ZGDCC46TxwYyvCfILtK3sLERNIAmLELeJ4zu3YzHlUb9jF/QGY7HP+2fVDxza8gc9HpxAi74DMf5r/EdFcwpqxoUmk6l1bB4P39mdP/ZZpyCHhBRSit7OFXo+B12ehLN/E/H7T8Cn+DtfGbfh4MHhBv/HXfdMYsJjTxVYxLBQ2UchMxqLJp4cUxbu7u7c29kJV2dHMnNM5JlV8iwWhjT3v+5U+ysDkXd3aoqrXocyfz4Az947FYABV45bsOAjJk36P1tX0ty5c8nIyKB27dqMGjWKmTNnFrjuI488UmDqdn4SEhUVhaLoaN7agaVLl/LOO+9wx8aJOGrtaBMQyuKhs7EcSYW29kW840JUD4pakmpNVVhqaiqurq6kpKRct3y7ELe780cOsuLVGQDYO7vQot8gmvXqh5uf9caamZqCKScHo6MT6UmXidq7m5T4S1w8dpj4s1F0GnU/Xe8ZU5kvoQDVYuHhTj6sOpDId/M/pN3A0bZ9rq6u2Nvb2wa7/ruFIjAw0HaDP3ToEH369GHAgAG2hQTBusBhfsG4efPmERQUROPGjSErmW2rFjP9f/N4spMdb2zJgGLOiFp7KZlHDp/hWLdmuOmvftZLz4rlg4MrmJfRA4CP1UkEOrji4dENf7+RuLi0KPX7tGz7KDRZh7mn/zHbtu0rf6XO7qt/49zuqo9Tx+sTLCFuF8W9f0sLixBVXHriZf6Y/xH+DRox8InpRPzxK/vWryHs5+X41W+IZ2AQJ8N2kJuVed257gGB9J80leZ9BxRy5cqjaDQs3n0ZgKEPPwk8adu3cOFCxo8fX6wWih9//JH4+Hi+++47vvvuO9v24OBgzpw5A1jHecyYMYOoqCh0Oh31ggJ4u58dj7bTw6/TYWjxFl/UXZmNk/evz3hO9n60qvMQHD7DAA87uvu+QnLKP8THb+DChW/x8R5EgwYvYmdX8nWBFI0BDQWfr9uoIfzjtAnfLTq0aEj++RRqngXnbrVKfH0hbifSwiJEFXYmIpxVc15H0WoZ+9aHeARYx3jk5WRzak8Yp8J2cPH4EWqHtqBBh87EnDrB0b+24Fe/Ia36D660gbXFkbDrZ7zWj+ec/0iCHl1YsU+edAY+bAUt74e7PivWKRsvp/LggdPMbxpMC2cHAu30GDQa1lxK5vEjZxju485HjYPQXRkwq6pmYmPXcCryHczmdOrWfZragQ+hKNpih/njzofQpu/krv4nr9t3YMcunH7JxKBai8e5DKyDS6/axb62EFWFtLAIcZuLOXmc1e+/Se3QFtzx6JM4e3rZ9umNdjTp2pMmVyql5mvYqRs9H5xQ0aGWSs6JPwHQJJzAnJeHtqKqtlrMcOIPcAkAtfizbGoZ9dhrFB67MlNIARy1GjLNFu7ydeejJkFor6mJoiha/P3vwtu7H5Gn3+Pkyf8RG7uKxo3/h4tzsxs8S0Ea7fUtLPladOnESaeDZCyPwdFsT+r6M6i5Zlz6B0ttFlEtSQuLEFWQqqp8NHYUWoOeRz9bjN5oV9khlbm8jCQS53TDlwtE+oyi3hNfV8wTXzoGn3YEl1rQ4xloV/wEz2RRuZiTy7msXM5n55JiMuOs03K/v0eBZKUwKSn7OHbsv6RnnCSo9sOEhDyFTnfz+jerdj+BLuV37uwXecNjLkSeJnnRMdzyrDOonHrUwnVQiCQt4rZR3Pu3rCUkRBWTm5VJcmw0prxc9Hb21TJZAdA7uuP86GrSzA7Uu7SSy7t/qZgnvlIXhZFflChZAdBpFILtjXT3cOaBAE8eD/LhwQDPIpMVAFfX1rRvv5p69Z7hwsXvCPtnEAkJW256jlZjRAs3Xck6sF5d/J5oQ7xdMgDp2y6SvDoS1VItPosKYSNdQkJUAdnp6Xw2+UHcfP1IjL5g295+6KhKjKr8OfjXJ+/5wyS/3RLPXx/E9IsGMxrMqgYLWsxosShaLOiwKDpURYdFo0e1felQNQZUjR60RlStAbQG0BlAZ0TRGtE6OOPXsBkagz1ojZAea31yc26Fv16NRk+d4Efx8R7I8eMvs//AI/j4DKFRw1cwGDyvO16rNaBVIM+Sh0F748Uovfz9sHuqB4c/20ytVC8ydsWgmiy4j2xgK0InxO1OEhYhKpHFYubcoQOs/J+1pLudswvu/rVoM3g4AQ0b41PIKr7Vjd7JA8MTW7iw6XPUvGwwZaOaclDMOaimXBRzDoo5F8x5KJZcFEseisWE1pSFoprQqCY0qhkNJrTWdAetciXdUSxoFOBIIU9sqLjlCP7NwSGYVq0WERu3mhMnXmdX2EDq1X0aO/vaaBQDGo0eRaNHZ8lCq0COKeumCQuAk7srrZ8ezNYvf6LJhUAy98Sh5pnxuKcxilaSFnH7kzEsQlQSU14eP77xXy4es95N/es34r7X3kGj1RbsAvjX/6LqtYMwCxz27/+V1Wv2Xd2qKKDVVdAA10p05sA+fnrzFdoNHUGP0feBKdvaqmLKAUUDblVjRk1ObgInjs/i0jULQV7LpEK7zjvxdPAp1vUsFgsH//cbnhnWv4PmYD1Bj3aUlhZRZcksISGquC2LPrclKwAxp47zwQPDy/+JFYWRL8wipApPeb5VidEXWDv3LYJbtKLb/eOs41YMlVvh90aMBi+aN/+E3NzLmM3ZqGouFksuFjWPiLg9/C9sDktLMJsJsCUrANqzeSQnX8bdw+smZwhR9UnCIkQlaT1wKB4Bgejtrh1Ue+20WKWwzSj865OycoNzChxydfvv8z8kOS6mVDHfDrLS0/j57VdxdPNgyFPPodEUv+5JZSpsDItdeibxJg155rxiX2f/njC8gVRtBln3ufLZ1o9pcKolz7V/TmYOievFn4CsJAjqWPj+9Hg4sso6QL2S/1+ShEWISuJVOxiv2sEV/rybF36OKSenwp+3ohzf8RcpcXFMmPs5do5OlR3OLckft5JrKf4AYf2aJMCZ7KHOtG3emcC03/nu6HfkWfJ4pt0z2Omq56wzUUpr/g/O74L2k6ytkKZcMOdYv5uy4NBK63GB7SCgchfblIRFiBpGZzRiyq34GTIV5cLRQ6iqxbbO0u1Mr7WONcot5oymS3ExuJms9VhadegMwKwuswj1CmV22Gx2Ru/klc6v0MG/Q/kELG4vFjMkn7P+fHqL9bHOzjrLTmsEnRGCusC5HZCXXbmxIgmLEDWO3mAkL7f6trBkpaVWdghlxqApWQtL1Oc7qYU3x5rGEnjNoo6jG46mrW9bXt3xKhP/mMiDTR7kmXbPoL1NustEGctKhrD5cHIDpMfBuF8gpEfhxyadhQ9bWFtdKpkkLELUMDqDoVp3CWm0Whp06FLZYZQJW5dQMVtYamVaV6h2rXP9jKK6rnVZOHAh3x/7nnd2v0N8VjxvdnuzyOnSoprJSoKv7oCUixDUCcasuHGyAtYWF7DOrqtkUulWiBpGZzSSV0TCsm3bNoYOHUpAQACKorBq1aoC+xVFKfRrzpw5tmOGDRtGUFAQdnZ2+Pv7M3bsWKKjowtcZ8WKFbRq1QoHBweCg4MLnF9SGclJXDpzmrzsrFJfo6qxtbAUM2FJ1aUDYDGZC92vUTSMaTKG93u9z5ZzW5iyaQoZeRk3raQrqpH0ePisGyScgEe3wdifoH6/m5+jM1q/myq/S0gSFiFqGL3BiKmILqGMjAxatmzJvHnzCt0fExNT4Ovrr79GURRGjbpambd3796sWLGC48ePs3LlSiIjI7n77rtt+3/77TfGjBnDY489xqFDh/j000/54IMP+OSTT0r1upb892m+ff5JLh47gt5oLNU1qpqSjmHJ1VgTlRslLPn6BvVlfv/5HEo4RKelnXhw3YPkWYo/E0ncRiwWiNoGPz1q7drJSoIHfgCv+sU7vwq1sEiXkBA1zPkjBwEY8uSzNzxm0KBBDBo06Ib7/fz8CjxevXo1vXv3pm7dq5V5p0+fbvs5ODiYF154gREjRpCXl4der+fbb79lxIgRPPbYYwDUrVuXGTNm8PbbbzNlypQST8E15+XRou9AmvTojVdgxc++Kg8lnSVk1uYnLEXXbWnv156FAxcy+pfRHEg4wNHLR2nh3aL0wYqqxWyCPV/Brk8h6Qx41oduT0PL+0pWNFFaWIQQ1UVcXBy//vorEydOvOExiYmJLFmyhC5duqDXW1sNcnJysLMrOMXW3t6eCxcucPbs2RLHodXrcXB1JbBxKHZOt/d05nwl7RKyaKxdO2oRLSz5Gns0ZtcDu6jjUocpm6YQHhdeukBF1ZCVBLEHYc2T8G4D+O15qN0JHl4PU/dAz2dLXuFZUazrc1WBFhZJWISoYZp2701gk2Zldr3Fixfj7OzMyJEjr9v3/PPP4+joiKenJ+fOnWP16tW2fQMGDOCnn35i06ZNWCwWTpw4wXvvvQdYu5xKSqfXY8qrXt0a+S0sxe2uURVrwmLOLV7CAuCod+S7wd/R0L0hj/zxCL9EVtCq2aLsJEbBptfh7Towv5u1dkq7CfDYXzDycwjuXKDAZInp7KSFRQhR8bQGQ5FjWEri66+/ZsyYMde1lgA8++yz7Nu3jz/++AOtVstDDz1kG+A5adIkpk6dyp133onBYKBTp07cd999AGg0Jf/TpNXpMVezhEWjaNApumK3sGQ0vzJNWV+ym5Or0ZX5/eZzZ907eXH7i3y096MSVdcVlWj3l/BxG9j+Pti5wcgv4bnT0Pcl8GteNs+hM1aJhEXGsAhRw+j0hjJrifjrr784fvw4y5cvL3S/l5cXXl5eNGzYkCZNmlC7dm127dpF586dURSFt99+mzfffJPY2Fi8vb3ZtGkTQIGxMMWl1RuqXcIC1laW4iYsvYcP43y7KDp7lbwwnF6r57UurxHsEswn+z7h19O/EuoVysRmEwn1Ci3x9UQ5M+XCxlesY1Q6Pga9XwQ71/J5Lp2d9fkqmSQsQtQwWr0ec17Z/PH56quvaNu2LS1btizyWIvFOhA0519TqrVaLbVq1QLg+++/p3Pnznh7e5c4Fq1ej9lUTROWEpTmr10rpNTPpSgKjzR/hO61uvPxvo/58/yfbD63mXsb3cvU1lNxNjiX+tqiDCWdhR8nQMx+GPQOdJh8a10+RZEWFiFEZdAZjJhyb35jT09P59SpU7bHUVFRRERE4OHhQVBQEGBdEv6HH36wjTu5VlhYGLt376Zbt264u7sTGRnJSy+9RL169ejc2VoyPiEhgR9//JFevXqRnZ3NwoUL+eGHH9i6dWvpXpdeVy2XHDBoDBXePdPIoxGf9P2EPHMeS44u4b3w91h/Zj2/3PULLgaXoi8gyoeqQvgi+GMm2HvAhN8hsAJWXdfZyaBbIUTF0+n1RY5h2bNnD61bt6Z1a+tiZ08//TStW7fm5Zdfth2zbNkyVFXl/vvvv+58BwcHfvrpJ/r27UujRo2YOHEiLVq0YOvWrRivqZGyePFi2rVrR9euXTl8+DB//vknHTqUbp0bra56trDotfoStbCU9XOPbzaeZ9o9Q3puOnf+dCef7PuEQwmHsKhFT50WZSjlAnx7F6ydBs1GwuN/V0yyAtLCIoSoHDpD0WNYevXqVWT108mTJzN58uRC9zVv3pzNmzff9HwvLy927tx582BLwDqGpRq2sJRgDEt5GRc6jkEhg/g04lOWHlvK5wc+x8vei87+nekc0Jk76tyBUVs9ivVVOaoK+76D318EgxM8uLLo6rRlTVpYhBCVobre2LXVcFozWLuEKjthAfBx8GFWl1lsu3cbXw/4mjvr3snJ5JP8d/t/GfDjADae3VjZIVY/SWdh6T2wZio0GQZP7Kz4ZAWu1GGRFhYhRAXTGQxYzGYsZjMabfVZrVenr37TmsHawlKVyubrNDra+7WnvV97AM6knOH98Pd5dtuzzOszjy61br7wpGoykf7XX5gTE3Hs1An9lQHX4l8u7LEmKzp7uG8pNB5SebFUkRYWSViEqGF0VyrNmvJyMWjtKzmaslNdZwnpNXpyzJV/s7iROq51eK/Xe0zbMo1pf07jw94f0jmgc6HHmpOTOdHp6j7Fzo6Ad97G5Y47Kircqi8xCjbOgiOroVYbuH8ZOF2/+naF0hkhO6VyY+AWu4TeeustFEVh2rRptm0LFiygV69euLi4oCgKycnJt3xNIUTZ0Rqs1VOr24wabTVtYbHT2VWJLqGb0Wv0vNvzXdr4tOGxjY+x8NDCQo9LWr4CAN8XZ9AofA9aD3cuL/iiIkOt2mIPwpf94MJuuPMD6yygyk5WoMq0sJQ6Ydm9ezeff/45LVoUXCwrMzOTgQMH8uKLL5bZNYUQZUentyYs1e3mrtXpMVXDsTkGraFKt7Dks9fZM6/vPCY0m8D74e+z5OiS647JjYrCrnlzPB56iKwDBzBFx+A5cUIlRFvFWCyw+yv4ehC4BsKjf0G7h+HKat2VTmeEKvA7WKqEJT09nTFjxvDFF1/g7u5eYN+0adN44YUX6NSpU5ldUwhRdnT5LSzV7OZuHcNiquwwypxRa7wtEhYArUbLU22eorVPa9765y1+PvkzZsvVdY30tWqRGxVFXkwMsf/7H/atWuE8cGAlRlwFbP8A3msIvz4Nze6Ccb+Ao2dlR1XQ7dzCMmXKFIYMGUK/fmU3Wrmk18zJySE1NbXAlxCiaPktLNWvS8hQLcewGLXGEncJbdu2jaFDhxIQEICiKKxatarAflVVefnll/H398fe3p5+/fpx8uTJAscMGzaMoKAg7Ozs8Pf3Z+zYsURHR9v2z5o1C0VRrvtydHTks36f0S+oHy/veJlRa0ax5OgS8ix5uN1zD4rBwKnefcg9FYnfa6+ilGeF1qru4I/W8SoZ8TB2FQz7GOyqYGE+XdWYJVTihGXZsmXs3buX2bNnl1kQpbnm7NmzcXV1tX3Vrl3CJbOFqKG0VwbdmqtdwqKvdkkYWBOWbHPJbhYZGRm0bNmSefPmFbr/nXfe4aOPPmL+/PmEhYXh6OjIgAEDyM6++jy9e/dmxYoVHD9+nJUrVxIZGcndd99t2//MM88QExNT4Ktp06aMHj0aR70jH/T+gO8Gf0ewSzDv7n6XoT8PZWNmOOkPDgLgbJ/GJAU4F1nvp1rKuAxr/g9WTrROU555Cer1ruyobkxrgCqwGGaJZgmdP3+ep556ig0bNhS6MmtplPaaM2bM4Omnn7Y9Tk1NlaRFiGKorl1C1bXSbWlaWAYNGsSgQYMK3aeqKnPnzmXmzJkMHz4cgG+++QZfX19WrVplWzF7+vTptnOCg4N54YUXGDFiBHl5eej1epycnHBycrIds3//fo4cOcL8+fNt21p6t+TDPh+yN24vn+3/jOe2PYe9VqXNMA07mp5EXXkHH/T6gH7BlVBbpDJkXIadH8Ou+dYkYMCb0OmJ8l0HqCxUkYSlRC0s4eHhXLp0iTZt2qDT6dDpdGzdupWPPvoInU6H2Wwu+iJldE2j0YiLi0uBLyFE0a4mLJX/B6gs6QzWWULV7RN7WY9hiYqKIjY2tkD3u6urKx07drxh5eHExESWLFlCly5d0OsLHwj65Zdf0rBhQ7p3737dvja+bVjQfwHz+s5j9sAPmf3adr4c8DUAL25/kZ9P/lzt/t0KSI+HDS/D3OYQtgA6Tob/C4fOUwokK4V1szVu3LjApXbu3EmfPn1wdHTExcWFHj16kJWVZdufmJjImDFjcHFxwc3NjYkTJ5Kenn5r8Wv1UAVmqpWohaVv374cPHiwwLaHH36Yxo0b8/zzz6MtRRGq8rimEOLGqu0YFt2Vri6TyVZrpjowao3klOGAx9jYWAB8fX0LbPf19bXty/f888/zySefkJmZSadOnVi7dm2h18zOzmbJkiW88MILN3xeRVHoEdjD9riDfwfCHgjjrX/e4uUdL7P94nZe7vwyrkbX0r60qkVV4fIpOPYrbH/fOhOo02PQacpNB9WGhoaycePVqsE63dXb9M6dOxk4cCAzZszg448/RqfTsX//fjSaq20PY8aMISYmhg0bNpCXl8fDDz/M5MmTWbp0aelfSxVpYSlRwuLs7EyzZs0KbHN0dMTT09O2PTY2ltjYWNtKrwcPHsTZ2ZmgoCA8PDwAa5Jy1113MXXq1GJdUwhRdrS2ac3VLGHJH5uTl1etEhaD1kCOpXJmaDz77LNMnDiRs2fP8uqrr/LQQw+xdu3a6wbK/vzzz6SlpTFu3LgSXd9B78BrXV+ja62uvLrzVe7+5W5md5tNO792ZfkyKpaqwuk/YdNrEL3XOsOm0SAY/F6xZv/odDr8/PwK3Td9+nSefPLJAolho0aNbD8fPXqU9evXs3v3btq1s76HH3/8MYMHD+bdd98lICCgdK9Ja6gSLSxlvpbQ/Pnzad26NZMmTQKgR48etG7dmjVr1tiOiYyMJCEhoayfWghRDDrDlUq31a2FJT9hqWbjWMq6cFz+zTAuLq7A9ri4uOtulF5eXjRs2JD+/fuzbNky1q1bx65du6675pdffsmdd955XatNcQ2oM4CVQ1dSy6kWE/+YyMf7Pq5SyxEUW24mrHgIvh1h7eq573t4LgpGLyr2VOWTJ08SEBBA3bp1GTNmDOfOnQPg0qVLhIWF4ePjQ5cuXfD19aVnz55s377ddu7OnTtxc3OzJSsA/fr1Q6PREBYWVvrXdTt2CRXmzz//LPB41qxZzJo166bnnDlzpkTXFEKUHY1Wh6Joql3huOpaEM+gNZBtykZV1TKZAhwSEoKfnx+bNm2iVatWgHXSQlhYGI8//vgNz7NYLIC1pMS1oqKi2LJlS4EPpaXh7+TPV3d8xVeHvuLjfR+z4MACZnefzZ1177yl61aIv96DiKWQkQB5mTDqK2g2qsSDaTt27MiiRYto1KgRMTExvPrqq3Tv3p1Dhw5x+vRpwHqPfffdd2nVqhXffPMNffv25dChQzRo0IDY2Fh8fApWxtXpdHh4eFzX3VciWgOoZrCYQVN5wzRkLSEhahhFUdAa9JhyK78QVFnKH8NS3WY/2WntUFExWUzoi1n5ND093dYtD9akIiIiAg8PD4KCgpg2bRpvvPEGDRo0ICQkhJdeeomAgABGjBgBQFhYGLt376Zbt264u7sTGRnJSy+9RL169ejcueA6QV9//TX+/v43nJVUElqNlsktJtPapzUTfp/AjL9m8E/MPzzV5ik87atYMTVVtS5QuP972PMV+DSFtuOgzTjwrFeqS177HrZo0YKOHTsSHBzMihUraNKkCQCPPvooDz/8MACtW7dm06ZNfP3112VaauQ6WuuHAcx5krAIISqWTm+odrOErh3DUp0Yrtwsss3ZxU5Y9uzZQ+/eV+t65JeAGDduHIsWLeK5554jIyODyZMnk5ycTLdu3Vi/fr2ttISDgwM//fQTr7zyChkZGfj7+zNw4EBmzpyJ0Wi0XddisbBo0SLGjx9fphMk2vu1J2JsBD+e+JGPIz7mj7N/0DOwJ4+2fJS6rnXL7HlKzZQLW96Avz8ErdE6PbnzlDJ/Gjc3Nxo2bMipU6fo06cPAE2bNi1wTJMmTWzdRn5+fly6dKlgqCYTiYmJNxwXUyz5v3fmXNCXTUmT0pCERYgaSGcwVLsxLLpqmrAYtdYEIcecgzPOxTqnV69eN50mrCgKr732Gq+99lqh+5s3b87mzZuLfB6NRsP58+eLFVNJaTVa7m18LwPqDODzA5/z3dHvWBe1jsktJjMudBwuhkooZWGxQORm+P1FuHwS2k2EQe+Atnxupenp6URGRjJ27Fjq1KlDQEAAx48fL3DMiRMnbC0znTt3Jjk5mfDwcNq2bQvA5s2bsVgsdOzYsfSBXNvCUokkYRGiBtLpDdV2llB1aznKT1iq+orN5cXNzo3nOzzPmCZjWHJ0Cb/88wd5X9ehedsQ2g+ui5uPQ/kHkZkIe76G8EWQch4C28Oj28CveZk+zTPPPMPQoUMJDg4mOjqaV155Ba1Wy/3334+iKDz77LO88sortGzZklatWrF48WKOHTvGjz/+CFhbWwYOHMikSZOYP38+eXl5TJ06lfvuu6/0M4TgmoSlcn8HJWERogaqjmXsq2uXUH7CUtLy/NVNoHMgz3d4nkapbbm4T8OJXZc4sesSLfoE0qxHLYwOehxcDGX2fKZcM2cPxBHzxyo65L2FQZMNLUZbx6gEti+X6rQXLlzg/vvv5/Lly3h7e9OtWzd27dqFt7c3YF1cODs7m+nTp5OYmEjLli3ZsGED9epdHTOzZMkSpk6dSt++fdFoNIwaNYqPPvro1gK7tkuoEknCIkQNpDMYqt3gVNssoWo2rbmmt7D8m6O9A5BNj6dqk31ax74/znFg8wUAnD3tqNvKm/ptffANcSnxrCpTnplzhxM5FX6JMwcSyMsxA40J7jyF2qMmgJN32b+gayxbtqzIY1544YWbFujz8PC4tSJxhZEuISFEZdEZDNWuJaK6t7CUZXn+25nRqAeyMSsm2g9pQLOetYiLSsWUa+HiiSRO7I5j/6bzOHkYqd3YA51eg86gxcXLDmdPexQNGO316I1a0pOySb2cTUZyDvHn04g+mUxethmPAEda3xFEQC0Lq+afxezbutyTlSpNIy0sQohKotVXv0G31XVasy1hKcPy/Lczezs7II2sHGsXmb2TgTrNvQCo39aH7vc2JOZkMqfCLxF3JhWLRSUv20R6Yg4Wy/UDkRWNgoOLAXc/B9rcEUTdVj54BDgCkB1vnXFjyTNVzIurqqRLSAhRWXR6fbW7sVfXFpb8ac3SwmJlf2VadVZ24e+HRqNQq5E7tRq5F9huMVvISMlFVVVys0zk5VhwcDHg5GFEqy286LvGYH0uc41PWKRLSAhRSXR6AzlZmZUdRpnSXlkkrrqNYbHTWeteyBgWK/srtWJyckr2fmi0Gpw9SlZDRGvMT1jMJTqv2qkis4TKfC0hIUTVVx3HsCiKcmX2U/V6XdcWjhPgaGcPQE5O+f87awzW995iquktLFWjS0gSFiFqIK3BUO1K84N1HEt1a2GRWUIFOdhb667kVMAYLEWjQUMe5jxLuT9XlVZFuoQkYRGiBqqOpfmherYcaRQNeo1eWliucLzSJZSbUzGtHlrFhNkkXUIAVPI4KklYhKiBrDf26veJvTq2sIC1lUVaWKy0Oi1mxURebkUmLDW8hUV3Zf2oSp6pJgmLEDWQVm8gr5pNawbQ6nXVbro2WBMWmSV0lVlTcQmLRjFLwnJl4Demym3lk4RFiBpIp9djroY39urcwpJdyTeLqsSiNWGqoJk7Wo0Zi+nGC0nWCFodaHSSsAghKp7OYJQxLLcRg9YgXULXsGjNmHIrptVDKy0sVjp7yJOERQhRwXQGffWdJVQNExY7nZ10CV3DojVhzq2YVg+txoK5ho+5BazjWKSFRQhR0XQGI6rFgqWa/SXW6vXVsuXIoDVIwnINiyEPS07Zr5ZcGK3GjNlcw7uEwDqORRIWIURFyy9jX93K8+v01bOFRQbdFqQazKg5FXP70mhULNUrry8dfeUnLFKaX4gaSKe31lU4/OdG7J1d0BmM6PR6dAYjWr0ejU6HTq9Hq9Oj1evR6nRXvlt/VjRV87OOVl99B93KGJZrGM2QbqyQp9JqLJhreKFbwNrCUsljWCRhEaIGcvP1Q2+0Y/PCz0t1vkarvZrM5Cc0tuTmmgTn348LSYB0VxKk/J+vvZ7OaERvMKIzGtEZDOiNRnQGo/W70YhGoy0Ql1anJ7earZEEV2YJSeE4G529Bi5riz6wDGg1KhYZc1sluoQkYRGiBvIKqsOT3/yIxWzGlJeLKffql9mUh8VkwpSXhzkvD7MpD7PJdPXnvBs8zv/5349NeeRk5tj2ma5st5hMtp+vfYxa/PECWp2uQFKTmZKCV9D/t3f/QVFddxvAn3PuworCSiASJYKx0RBjX01CfpQ2bSVSg42+JOlkptYQpIytbWzTSWxTzR/YaZyknXRSk0wVq9FpmzadJrF1EjOMGXU0mYYgFAewaslAXwQNxkRADMvu3u/7x8LiIgiLe7nL5fnM7MD9uefkq9nHc+7ee4N1/+Fs4jbc6OzptLsZMcM92QV/T9yYvJc2BIHA2FwvE9MYWIjITtowEG8kIL73gXJ2ExGYgUAo7Ph9PfB7vfB5vfD3DPjp9cLX471se8b8/7G7G1E3OW4yPmz8EL858hu4tAtxOq7/ZfT/3rfNpV0wlAFDG3ApFwxtwFBG2HpDGYjTcUNuG3gOpWLnQ3tyohsX/WM1JQQ47HmaoxMD3xJiYCGimKGU6p0OcgExEqJiwTdnfxO1Z2txsPkgfKYPPtMHv+nv/xnwwS/WXmihlQ4LMgMDTZwRB7fhDr3ijfhgPZUBDR36/dKfU/5vBq59byECk7vhzfgEUApKBf8c9P1EaLl/3cfN7ZhhXoOLn3+OyQnW/jkxDOBCxyScfGNPaF1YdgvLcf0LM9IDSEyU8PVGPJCQDExKBuKnBJ+CrOMAbQBiBkcXxQQgQy9j4AjkJQ0YqmHRWs9rWIiI6ErunH4nXv/f16+4jylmWIgJSAABM4CABOA3/aF1g23rW/aL/7LlQfcz/Zdt85k+dPu70WP2oNvfDZ/pgykmTDEhIvCbfvSgB6ZpwkRw3bV1dwAAjIuTIKcTAFHBj2MBIL0flKIA6f3YFABQ8EgaOqeeheGy/uJvT4oLJ89ch337Ijsua9IB5CW/aE2j7DJ3ia1vz8BCROQAWmnEG/GI73uy7jjwxtEqJM9LwOKiW+xuypDuWvsIbr/Y1bsk/QMcIr2/SmhT3/VXe3c0wD/5QaB4Xfg1WX4v0N0OdJ8HeroA09/7CgRHNZRGcEhJ9y6rAcu920MuOXfYtV9Xs37gf4FLVqTZWycGFiIisoU2FMwYvymb0hpxiUkRHWPEx0OUBiZNvXxj0nVRatnEE5s3UyAiIscbD4FlNLShYJrO65fdGFiIiMgW2tCODCxKwZH9shsDCxER2SI4wuK8u7JpQ0EiuJ8QjQwDCxER2cJw6pSQdma/7MbAQkREttCGcuSTkJVWEF7DEnUMLEREZIvgNSzOmxJiYLEGAwsREdnCqd8SUprXsFiBgYWIiGzh2MCiwCc8W4CBhYiIbOHYrzVzSsgSDCxERGSL4LdpnDcUoRWnhKzAwEJERLaIdEro0KFDWL58OdLT06GUwt///vch912zZg2UUvjtb38bWtfU1ISSkhLMnj0bCQkJuPHGG1FaWoqenp7QPhs3brzk6dD9rylTpoy4nRxhsQafJURERLaINLB0dXVh4cKF+O53v4uHHnpoyP12796NDz74AOnp6WHrjx8/DtM0UVZWhjlz5qCurg6rV69GV1cXnn/+eQDAunXrsGbNmrDjFi9ejDvvvHPE7VRqwLMFKSoYWIiIyBaR3ul26dKlWLp06RX3aWlpwY9+9COUl5fj/vvvD9uWn5+P/Pz80PIXvvAFnDhxAlu2bAkFlsTERCQmJob2OXr0KI4dO4atW7eOuJ0cYbEGp4SIiMgW2tBRfUigaZooLCzET3/6U8yfP39Ex7S3tyMlJWXI7du3b8dNN92Er371qyNuh9J8+KEVGFiIiMgW0f5a869+9Su4XC78+Mc/HtH+DQ0NeOmll/D9739/0O3d3d149dVXUVJSElE7tAZHWCzAKSEiIrJFNG/NX1VVhc2bN6O6uhpKqWH3b2lpQX5+Ph5++GGsXr160H12796Nzs5OFBUVRdQWpRSvYbEAR1iIiMgW0bw1/+HDh9HW1obMzEy4XC64XC7897//xZNPPokbbrghbN/W1lbk5ubiy1/+MrZt2zbkObdv345ly5bhuuuui6gtvIbFGhxhISIiW0RzSqiwsBB5eXlh6+677z4UFhaiuLg4tK6lpQW5ubnIzs7Gzp07ofXg/25vbGzEgQMHsGfPnojbohSnhKzAwEJERLbQhgIEME2B1sNP41y4cAENDQ2h5cbGRtTU1CAlJQWZmZlITU0N2z8uLg7Tp09HVlYWgGBYWbRoEWbNmoXnn38eZ8+eDe07ffr0sGNfeeUVzJgxY9hvJQ1GaQXmlehjYCEiIlsYRjCkmAETWhvD7n/kyBHk5uaGlp944gkAQFFREXbt2jXs8fv27UNDQwMaGhowc+bMsG2X3pnWNE3s2rULq1atgmEM366BOCVkDQYWIiKyhTaC0zFmQIC44fdftGhRRLe8b2pqCltetWoVVq1aNXy7tEZzc/OI3+fy43lrfivwolsiIrKFDo2wOOzDXQHivEck2Y6BhYiIbOHUwKI5JWQJBhYiIrJF/5SQs4YjlGJgsQIDCxER2cKpIyxK88ZxVmBgISIiWzg2sPA+LJZgYCEiIlv0TQkFnDYlpBVMDrFEHQMLERHZom+ExWmjEVoHb4jHrzZHFwMLERHZwrFTQr2frE4LYnZjYCEiIls4N7D0jhw5q1u2Y2AhIiJbGA7+WjPAEZZoY2AhIiJb9I2wBBw3whL8aTKwRBUDCxER2cKxU0KKU0JWYGAhIiJbhD380EG05pSQFRhYiIjIFv0jLA67hoWBxRIMLEREZAunTgmF+sXAElUMLEREZAvHBhbtzH7Z7aoCy3PPPQelFH7yk5+E1m3btg2LFi2Cx+OBUgrnz58f9jxbtmzBggUL4PF44PF4kJOTg3feeedqmkZERDGu/4PdYVNCDr2Dr91GHVgqKytRVlaGBQsWhK2/ePEi8vPzsWHDhhGfa+bMmXjuuedQVVWFI0eO4N5770VBQQHq6+tH2zwiIopxyqEjERxhsYZrNAdduHABK1euxO9//3s888wzYdv6RlsOHjw44vMtX748bHnTpk3YsmULPvjgA8yfP380TSQiohinlII2lOM+2EOBhSMsUTWqEZbHHnsM999/P/Ly8qLdHgQCAbz22mvo6upCTk7OkPt5vV50dHSEvYiIaHxxYmDhlJA1Ih5hee2111BdXY3KysqoNqS2thY5OTno7u5GYmIidu/ejVtuuWXI/Z999ln84he/iGobiIhobGlDI+Cwa1g4JWSNiEZYmpub8fjjj+PVV1/FpEmTotqQrKws1NTUoKKiAj/4wQ9QVFSEY8eODbn/+vXr0d7eHno1NzdHtT1ERGQ9J46w8GvN1ohohKWqqgptbW24/fbbQ+sCgQAOHTqEl19+GV6vF4ZhjKoh8fHxmDNnDgAgOzsblZWV2Lx5M8rKygbd3+12w+12j+q9iIgoNjgxsPDGcdaIKLAsXrwYtbW1YeuKi4tx880346mnnhp1WBmMaZrwer1ROx8REcWeYGDhlBANL6LAkpSUhC9+8Yth66ZMmYLU1NTQ+jNnzuDMmTNoaGgAELw2JSkpCZmZmUhJSQEQDD4PPvgg1q5dCyA4vbN06VJkZmais7MTf/7zn3Hw4EGUl5dfdQeJiCh2aUM77oOdU0LWGNXXmq9k69atYRfDfu1rXwMA7Ny5E6tWrQIAfPTRR/jkk09C+7S1teHRRx/F6dOnMXXqVCxYsADl5eX4xje+Ee3mERFRDDGcPCXksH7Z7aoDy8D7rWzcuBEbN2684jFNTU1hyzt27LjaZhAR0TjkxGtYtO59CjVHWKKKzxIiIiLbBKeEHHYNC6eELMHAQkREtnHmCAunhKzAwEJERLZxYmBRHGGxRNQvuiUiIhopbSicqDgD92QXDJeGdikYLh16aUPBiNMwDAV96fq+/QwNI05BG33bVO/23t8NHboIdsz6FHqWkLOmuuzGwEJERLa54X+uhfeiH6dOfAYzIAj4TAT8JgIBEwG/wPSbVz0Co7WC7g09Q4aiy8JOb0iK6w1FrksDU/jxl25zxWkoxSkhKzCwEBGRbW7Ny8SteZlX3EdMCYaZviDjE5iB3mDj713vN2EOXO49ZtD1vv5Q1L9PcNnvDcB70Tfo+wx2rqG43NG7mSoxsBARUYxTWsHQwamhWCOm9AefvtEhvwkIMDUtwe7mOQoDCxER0SgpreDSBlxxAJhPLBV7cZWIiIhoAAYWIiIiinkMLERERBTzGFiIiIgo5jGwEBERUcxjYCEiIqKYx8BCREREMY+BhYiIiGIeAwsRERHFPAYWIiIiinkMLERERBTzGFiIiIgo5jGwEBERUcxzzNOaRQQA0NHRYXNLiIiIaKT6Prf7PseH4pjA0tnZCQDIyMiwuSVEREQUqc7OTkydOnXI7UqGizTjhGmaaG1tRVJSEpRSIzqmo6MDGRkZaG5uhsfjsbiFdLVYr/GDtRpfWK/xxWn1EhF0dnYiPT0dWg99pYpjRli01pg5c+aojvV4PI4o+kTBeo0frNX4wnqNL06q15VGVvrwolsiIiKKeQwsREREFPMmdGBxu90oLS2F2+22uyk0AqzX+MFajS+s1/gyUevlmItuiYiIyLkm9AgLERERjQ8MLERERBTzGFiIiIgo5jGwEBERUcxzfGA5efIkCgoKcO2118Lj8eCee+7BgQMHQtvPnTuH/Px8pKenw+12IyMjA2vXrr3iM4mamppQUlKC2bNnIyEhATfeeCNKS0vR09MzFl1yLCtqBQCffvopVq5cCY/Hg+TkZJSUlODChQtWd8fxhqvX0aNHsWLFCmRkZCAhIQHz5s3D5s2br/q8FDmragUAb7/9Nu6++24kJCTgmmuuwQMPPGBRLyYOK+sFAF6vF7feeiuUUqipqbGgB9ZwfGBZtmwZ/H4/9u/fj6qqKixcuBDLli3DmTNnAATvkFtQUIA9e/bg5MmT2LVrF959912sWbNmyHMeP34cpmmirKwM9fX1eOGFF7B161Zs2LBhrLrlSFbUCgBWrlyJ+vp67Nu3D2+99RYOHTqE733ve2PRJUcbrl5VVVVIS0vDn/70J9TX1+Ppp5/G+vXr8fLLL1/VeSlyVtXqjTfeQGFhIYqLi3H06FG8//77+M53vjMWXXI0q+rV52c/+xnS09Ot7II1xMHOnj0rAOTQoUOhdR0dHQJA9u3bN+RxmzdvlpkzZ0b0Xr/+9a9l9uzZo27rRGdVrY4dOyYApLKyMrTunXfeEaWUtLS0RKfxE9Bo6/XDH/5QcnNzo35eGppVtfL5fHL99dfL9u3bo9reic6qevXZu3ev3HzzzVJfXy8A5F//+lc0mj0mHD3CkpqaiqysLPzhD39AV1cX/H4/ysrKkJaWhuzs7EGPaW1txZtvvomvf/3rEb1Xe3s7UlJSotHsCcmqWv3zn/9EcnIy7rjjjtC6vLw8aK1RUVER9X5MFKOpFzD835PRnpeGZlWtqqur0dLSAq01brvtNsyYMQNLly5FXV2dFd2YMKyqFwB8/PHHWL16Nf74xz9i8uTJ0W669exOTFZrbm6W7OxsUUqJYRgyY8YMqa6uvmy/b3/725KQkCAAZPny5fL555+P+D3+85//iMfjkW3btkWz6ROOFbXatGmT3HTTTZetnzZtmvzud7+LavsnmpHWq8/7778vLpdLysvLo3peGp4VtfrLX/4iACQzM1Nef/11OXLkiKxYsUJSU1Pl3LlzVnRjwrCiXqZpSn5+vvzyl78UEZHGxkaOsIyFn//851BKXfF1/PhxiAgee+wxpKWl4fDhw/jwww/xwAMPYPny5Th9+nTYOV944QVUV1fjH//4Bz766CM88cQTI2pLS0sL8vPz8fDDD2P16tVWdHdci6Va0fCsqBcA1NXVoaCgAKWlpViyZMmQ7x/peScyu2tlmiYA4Omnn8a3vvUtZGdnY+fOnVBK4W9/+5tl/R6v7K7XSy+9hM7OTqxfv97KblrLzrQ0Wm1tbfLvf//7ii+v1yvvvvuuaK2lvb097Pg5c+bIs88+O+T5Dx8+LACktbX1iu1oaWmRuXPnSmFhoQQCgaj0zWnsrtWOHTskOTk5bJ3P5xPDMOTNN9+8+g46jBX1qq+vl7S0NNmwYcOw7z/aPwcTkd212r9/vwCQw4cPh62/6667RnT8RGN3vQoKCkRrLYZhhF4AxDAMefTRR6PaV6u47I1LozNt2jRMmzZt2P0uXrwIIPjtkktprUP/OhhM3zav1zvkPi0tLcjNzQ39q2Lge1CQ3bXKycnB+fPnUVVVFZr/3b9/P0zTxN133z2iPkwk0a5XfX097r33XhQVFWHTpk1ROy/ZX6vs7Gy43W6cOHEC99xzDwDA5/OhqakJs2bNiqQrE4Ld9XrxxRfxzDPPhJZbW1tx33334a9//ev4+X+h3YnJSmfPnpXU1FR56KGHpKamRk6cOCHr1q2TuLg4qampERGRt99+W1555RWpra2VxsZGeeutt2TevHnyla98JXSeiooKycrKklOnTomIyKlTp2TOnDmyePFiOXXqlJw+fTr0otGxqlYiIvn5+XLbbbdJRUWFvPfeezJ37lxZsWLFmPfRSUZSr9raWpk2bZo88sgjYX9H2traQucZWK+RnJciY1WtREQef/xxuf7666W8vFyOHz8uJSUlkpaWJp9++umY99MprKzXpcbjNSyODiwiIpWVlbJkyRJJSUmRpKQk+dKXviR79+4Nbd+/f7/k5OTI1KlTZdKkSTJ37lx56qmn5LPPPgvtc+DAAQEgjY2NIiKyc+dOATDoi0bPilqJiJw7d05WrFghiYmJ4vF4pLi4WDo7O8ewZ840XL1KS0sH/Tsya9as0D6D1Wu481LkrKpVT0+PPPnkk5KWliZJSUmSl5cndXV1Y9gzZ7KqXpcaj4FFiYiMzVgOERER0ejwwgsiIiKKeQwsREREFPMYWIiIiCjmMbAQERFRzGNgISIiopjHwEJEREQxj4GFiIiIYh4DCxEREcU8BhYiIiKKeQwsREREFPMYWIiIiCjmMbAQERFRzPt/+MxxlCgcNn8AAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for c in [21,61]:\n",
    "    for u in countyUnitList[c]:\n",
    "        if u in borderUnits:\n",
    "            plotPoly(unitGeom[u])\n",
    "            plotCenter(u,unitGeom[u])\n",
    "print(\"Lets ID borderUs near Sandusky Bay, in case there are any we want to drop\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "9e6949b4-19ab-4c39-8140-7b16bb2dc34b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dropping units {1059} from the border set; they only border Sandusky Bay, not the true exterior\n"
     ]
    }
   ],
   "source": [
    "falseBorderUset = {1059}\n",
    "print(\"dropping units\",falseBorderUset,\"from the border set; they only border Sandusky Bay, not the true exterior\")\n",
    "borderSet = set(borderUnits).difference(falseBorderUset)\n",
    "borderUnits = list(borderSet)\n",
    "\n",
    "isBorder = [0]*nUnits\n",
    "for u in range(nUnits):\n",
    "    if u in borderUnits:\n",
    "        isBorder[u] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "id": "1d7c2953-ed12-4349-8f5b-c9ffbc185a87",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here, we identify 'border' units that aren't needed to define the map border\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{306} is the list of 1-neighbor 'border' units that can be eliminated from the border set\n",
      "... as they are enveloped on the border; the enveloping border unit has two other map-border neighbors\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 1 to remove these from the list of border units 1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Success! we removed {306} from the list of borderUnits\n"
     ]
    }
   ],
   "source": [
    "print(\"here, we identify 'border' units that aren't needed to define the map border\")\n",
    "canBeRemoved, powerNeighbors = set(), set()\n",
    "for u in borderUnits:\n",
    "    uNeighbors = list(borderSet.intersection(set(unitNbrs[u])) )\n",
    "    if len(uNeighbors) < 2:\n",
    "        plotPoly(unitGeom[u])\n",
    "        plotCenter(u,unitGeom[u])\n",
    "        uu = uNeighbors[0]\n",
    "        otherBorderNeighbors = set(unitNbrs[uu]).intersection(borderSet).difference({u})\n",
    "        if len(otherBorderNeighbors) > 1:  #this neighbor of our 1-border-neighbor border unit makes a border chain without the problem border unit\n",
    "            canBeRemoved.add(u)\n",
    "            powerNeighbors.add(uu)\n",
    "        plotCenter(uu,unitGeom[uu],6)\n",
    "        plotPoly(unitGeom[uu],0.5)\n",
    "        for uuu in set(unitNbrs[uu]).intersection(borderSet).difference({u}):\n",
    "            plotPoly(unitGeom[uuu])\n",
    "            plotCenter(str(uuu)+\"=N of\"+str(uu),unitGeom[uuu])\n",
    "        for uuu in set(unitNbrs[u]).difference(borderSet):\n",
    "                plotCenter(uuu+0.1,unitGeom[uuu],6)\n",
    "                plotPoly(unitGeom[uuu],0.1)\n",
    "        c = countyNo[unitTractList[u][0]]\n",
    "        #plotPoly(countyGeom[c] )\n",
    "        #plotCenter(c, countyGeom[c])\n",
    "        plt.show()\n",
    "if len(canBeRemoved) == 0:\n",
    "    print(\"Bueno! no 'border units' that could be eliminated from the border set\")\n",
    "else:\n",
    "    print(canBeRemoved,\"is the list of 1-neighbor 'border' units that can be eliminated from the border set\")\n",
    "    print(\"... as they are enveloped on the border; the enveloping border unit has two other map-border neighbors\")\n",
    "    yesRemove = input(\"enter 1 to remove these from the list of border units\")\n",
    "    if int(yesRemove) == 1:\n",
    "        canRemove = True\n",
    "        for uu in powerNeighbors:\n",
    "            testSet = (borderSet.difference(canBeRemoved)).difference({uu})\n",
    "            if not isContiguous(list(testSet),unitNbrs):\n",
    "                canRemove = False\n",
    "                print(\"We can't complete the border if unit\",uu,\"is not included in the ring\")\n",
    "        if canRemove:\n",
    "            borderSet = borderSet.difference(canBeRemoved)\n",
    "            borderList = list(borderSet)\n",
    "            borderUnits = list(borderSet)\n",
    "            print(\"Success! we removed\",canBeRemoved,\"from the list of borderUnits\")\n",
    "    else:\n",
    "        print(\"Fine, be that way.  Sheesh, I will keep them.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "id": "3b521a2c-e070-457e-a0ad-735b207d1fbc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "check for contiguity of border upon hypothetical removal of each border u\n"
     ]
    }
   ],
   "source": [
    "print(\"check for contiguity of border upon hypothetical removal of each border u\")\n",
    "for u in borderSet:\n",
    "    contig, _ = isContiguous(list(borderSet.difference({u}) ),unitNbrs )\n",
    "    if not contig:\n",
    "        print(\"border is not contiguous if we skip unit\",u)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8d7a790d-9889-4571-96ff-34d4e0b69119",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "id": "5add9c83-4d1d-41e3-8393-e31aab496c41",
   "metadata": {},
   "outputs": [],
   "source": [
    "date = \"12Jan\"\n",
    "nUnits = len(unitPop)\n",
    "unitNo = [u for u in range(nUnits)]\n",
    "onBorder = [0 for u in range(nUnits)]\n",
    "unitCPx, unitCPy = [unitCP[u].x for u in range(nUnits)], [unitCP[u].y for u in range(nUnits)]\n",
    "unitCountyNo = [countyNo[unitTractList[u][0]] for u in range(nUnits)]  #exactly correct; no county-straddling munis\n",
    "cantSplit = [0]*nUnits\n",
    "for u in range(nUnits):\n",
    "    if u in unsplittableUnits:\n",
    "        cantSplit[u] = 1\n",
    "for u in borderUnits:\n",
    "    onBorder[u] = 1\n",
    "nbrDF = pd.DataFrame( {\"unitNo\":unitNo,\"centroid x\":unitCPx,\"centroid y\":unitCPy,\"unitPop\":unitPop,\"onBorder\":onBorder,\n",
    "                       \"cantSplit\":cantSplit,\"unitNbrs\":unitNbrs, \"unitCountyNo\":unitCountyNo,\"unitTractList\":unitTractList} )\n",
    "outname = STATE+str(nDistricts)+\"_5cityUnitTopologies_\"+date+\".csv\" \n",
    "outpath = \"state_map_files/\"+outname\n",
    "nbrDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "id": "78564573-ce6d-4d0e-b2d4-3c33f25b0be6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Pull in the any-split Home Districts ...\n",
      "Now convert (approximately) to full VTD lists. We didn't store the VTDfrag lists, so use binary in-out if frac > 0.5\n",
      "Lets compare our true HDpops to this partial-based calculation\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "print(\"Pull in the any-split Home Districts ...\")\n",
    "infile = \"./2024state_HD_output/OH8941VRApatchedVTDs.csv\" #OH8941legisl60_1p5PatchedVTDs.csv\"\n",
    "HDdf = pd.read_csv(infile)\n",
    "HDvtdListString, partialString, fracString = HDdf[\"HDvtdList\"], HDdf[\"partials\"],HDdf[\"HDvtdFrac\"]\n",
    "HDCPx, HDCPy, HDwt = HDdf[\"centroid x\"],HDdf[\"centroid y\"], HDdf[\"HDweight\"]\n",
    "HDvTruePop = HDdf[\"HDvPop\"]\n",
    "HDCP = [Point(HDCPx[v], HDCPy[v]) for v in range(nVTDs)]\n",
    "hdCP = HDCP.copy() #nomenclature\n",
    "nHDs = len(HDvtdListString)\n",
    "HDvtdList = [ast.literal_eval(HDvtdListString[h]) for h in range(nHDs)]\n",
    "HDpartials = [ast.literal_eval(partialString[h]) for h in range(nHDs)]\n",
    "HDvtdFrac = [ast.literal_eval(fracString[h]) for h in range(nHDs)]\n",
    "print(\"Now convert (approximately) to full VTD lists. We didn't store the VTDfrag lists, so use binary in-out if frac > 0.5\")\n",
    "for h in range(nHDs):\n",
    "    for i, frac in enumerate(HDvtdFrac[h]):\n",
    "        if frac >= 0.5:\n",
    "            HDvtdList[h].append(HDpartials[h][i])\n",
    "print(\"Lets compare our true HDpops to this partial-based calculation\")\n",
    "HDvtdPop = [np.sum ([ tractPop[v] for v in HDvtdList[h] ] ) for h in range(nHDs) ]\n",
    "popRatio = [(HDvtdPop[h] + 0.0001) / (HDvTruePop[h] + 0.0001) for h in range(nHDs) ]\n",
    "plt.scatter([h for h in range(nHDs)], popRatio, label=\"converted to true pop\")\n",
    "plt.legend()\n",
    "plt.show()\n",
    "#HDvtdFracList  = [list() for h in range(nHDs)]  ##modified 11/24 - do not use VTD fragments\n",
    "#for h in range(nHDs):\n",
    "#    for v in HDvtdList[h]:\n",
    "#        for f in VTDchildren[v]:\n",
    "#            HDvtdFracList[h].append(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "1fbef9d8-35f8-49cf-bb3e-6d6acf517033",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "8941 786629.8666666667\n",
      "3\n"
     ]
    }
   ],
   "source": [
    "print(nHDs, aDP)\n",
    "print(np.min(unitPop))\n",
    "minDistrictPop, maxDistrictPop = 0.995*aDP, 1.005*aDP  #0.95, 1.05"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "id": "b08d6302-63ee-451f-ae11-d61c5440f425",
   "metadata": {},
   "outputs": [],
   "source": [
    "unitVTDlist = [unitTractList[u].copy() for u in range(nUnits) ] #nomenclature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "id": "9fe8940f-434d-405d-b52f-e17074715fcf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now snap each HD to units.  Each HD is assigned its home unit, then we build out whole units, then ...\n",
      "... we add units that were partially included, biasing toward close, mostly full ones\n",
      "working on snapping HD 0 in unit 165 to whole units, secs elapsed = 0\n",
      "working on snapping HD 2002 in unit 1480 to whole units, secs elapsed = 26\n",
      "working on snapping HD 4004 in unit 3733 to whole units, secs elapsed = 57\n",
      "HD 4029  has only 0.016 pop/aDP. We will swell by nearest munis to shore it up\n",
      "working on snapping HD 6006 in unit 2447 to whole units, secs elapsed = 84\n",
      "HD 7367  has only 0.015 pop/aDP. We will swell by nearest munis to shore it up\n",
      "working on snapping HD 8006 in unit 775 to whole units, secs elapsed = 117\n"
     ]
    }
   ],
   "source": [
    "\n",
    "print(\"Now snap each HD to units.  Each HD is assigned its home unit, then we build out whole units, then ...\")\n",
    "print(\"... we add units that were partially included, biasing toward close, mostly full ones\")\n",
    "minSnapFrac, minEligFrac = 0.667, 0.1 #we auto-add contig munis at least this full in HDvtdList\n",
    "homeU, HDvPop, HDunitList = [-888]*nHDs, [0.]*nHDs, [list() for h in range(nHDs) ]\n",
    "popHDlist = list()\n",
    "for u in range(nUnits):\n",
    "    origArea = np.sum( [tractArea[v] for v in unitVTDlist[u] ] )\n",
    "    origL = origArea ** 0.5  #characteristic local district diameter\n",
    "    for v in unitVTDlist[u]:\n",
    "        homeU[v] = u\n",
    "for v in range(nHDs):\n",
    "    if HDvTruePop[v] > 0:\n",
    "        popHDlist.append(v)\n",
    "\n",
    "snapThresh = 0.6  #0.8, 0.9 for blocky.  Closer to 0.5 for small units\n",
    "startTime = time.time()\n",
    "for nh,h in enumerate(popHDlist):\n",
    "    if nh%2000 == 0:\n",
    "        print(\"working on snapping HD\",h,\"in unit\",homeU[h],\"to whole units, secs elapsed =\",int(time.time()-startTime) )\n",
    "    currPop, addedUset = unitPop[homeU[h]], { homeU[h] }\n",
    "    useFrac = [0.]*nUnits\n",
    "    for v in HDvtdList[h]:\n",
    "        useFrac[homeU[v]] += tractPop[v] / unitPop[homeU[v]]\n",
    "    shouldAddUset, hasFracUset = set(), set()\n",
    "    for u in range(nUnits):\n",
    "        if useFrac[u] > minSnapFrac :  #munis more than 2/3 captured should be snapped if contig path found\n",
    "            shouldAddUset.add(u)\n",
    "        if useFrac[u] > minEligFrac :  #munis that were at least 10% captured are eligible to be snapped\n",
    "            hasFracUset.add(u)\n",
    "    shouldAddUset = shouldAddUset.difference(addedUset)  #at this point, this knocks out just the home muni\n",
    "    nJustAdded = 1\n",
    "    while nJustAdded > 0 and currPop < aDP:  #this block -- add all mostly full HDs that are contig to growing list\n",
    "        nJustAdded = 0\n",
    "        canAddUset = set()\n",
    "        for u in addedUset:  #building all neighbors of in-HD munis\n",
    "            canAddUset = canAddUset.union(set(unitNbrs[u]) )\n",
    "        canAddUset = canAddUset.intersection( shouldAddUset.difference(addedUset) ) #whittling to eligible list\n",
    "        for u in canAddUset:\n",
    "            if currPop + snapThresh * unitPop[u] < maxDistrictPop: #prevent big overadds.  0.6, 0.8, 0.9 is adjustable\n",
    "                currPop += unitPop[u]\n",
    "                addedUset.add(u)\n",
    "                nJustAdded +=1\n",
    "            if currPop > minDistrictPop:  #it's OK if we go over; we'll trim back later\n",
    "                break\n",
    "    # OK, we've added the 2/3 full munis.  Now add more contiguous partials if needed\n",
    "    eligibleSet = hasFracUset.difference(addedUset)\n",
    "    for u in list(eligibleSet):\n",
    "        if currPop + snapThresh * unitPop[u] > maxDistrictPop:\n",
    "            eligibleSet.remove(u)\n",
    "    contigAddableSet = set()  #the eligible units adjacent to the current (growing) set of units\n",
    "    for u in addedUset:\n",
    "        contigAddableSet = contigAddableSet.union(set(unitNbrs[u]).intersection(eligibleSet))\n",
    "    while currPop < minDistrictPop and len(contigAddableSet) > 0:  #add close, mostly used munis\n",
    "        canAddUlist = list(contigAddableSet)\n",
    "        canAddScores = [ unitCP[u].distance(HDCP[h])/origL * (1. - useFrac[u]) for u in canAddUlist]\n",
    "        addIdx = canAddScores.index(np.min(canAddScores))\n",
    "        u = canAddUlist[addIdx]\n",
    "        currPop += unitPop[u]\n",
    "        addedUset.add(u)\n",
    "        contigAddableSet.remove(u)\n",
    "        eligibleSet.remove(u)\n",
    "        contigAddableSet = contigAddableSet.union(set(unitNbrs[u]).intersection(eligibleSet))\n",
    "        for u in list(contigAddableSet):\n",
    "            if currPop + 0.8 * unitPop[u] > maxDistrictPop: #prevent big overadds\n",
    "                contigAddableSet.remove(u)\n",
    "    if currPop < 0.2 * aDP:\n",
    "        print(\"HD\",h,\" has only\",r3(currPop/aDP),\"pop/aDP. We will swell by nearest munis to shore it up\")\n",
    "        canAddUset = set(unitNbrs[homeU[h]])\n",
    "        for u in addedUset:\n",
    "            canAddUset = canAddUset.intersection(unitNbrs[u])\n",
    "        canAddUset = canAddUset.difference(addedUset)\n",
    "        while currPop < minDistrictPop and len(canAddUset) > 0:  #add close munis, biasing towards highly used\n",
    "            canAddUlist = list(canAddUset)\n",
    "            canAddScores = [ unitCP[u].distance(HDCP[h])/origL * (1. - useFrac[u]) for u in canAddUlist]\n",
    "            addIdx = canAddScores.index(np.min(canAddScores))\n",
    "            u = canAddUlist[addIdx]\n",
    "            currPop += unitPop[u]\n",
    "            addedUset.add(u)\n",
    "            canAddUset.remove(u)\n",
    "            for uu in unitNbrs[u]:\n",
    "                if useFrac[uu] > 0 and uu not in addedUset:\n",
    "                    canAddUset.add(uu)\n",
    "            for u in list(canAddUset):\n",
    "                if currPop + 0.9 * unitPop[u] > maxDistrictPop: #prevent big overadds\n",
    "                    canAddUset.remove(u)\n",
    "\n",
    "    HDvPop[h] = currPop\n",
    "    HDunitList[h] = list(addedUset)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "id": "6ca0e286-f4bc-4153-8e53-42e5b6757339",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "lets plot our unit-snapped HD pops vs. orig pops\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "and compute current unit usage with these whole-unit, possibly discontig HDs\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"lets plot our unit-snapped HD pops vs. orig pops\")\n",
    "plt.scatter([HDvtdPop[t] for t in popHDlist], [HDvPop[t] for t in popHDlist])\n",
    "plt.axhline(aDP,ls=\"--\")\n",
    "plt.show()\n",
    "print(\"and compute current unit usage with these whole-unit, possibly discontig HDs\")\n",
    "unitUse = [0.]*nUnits\n",
    "for h in popHDlist:\n",
    "    for u in HDunitList[h]:\n",
    "        unitUse[u] += nDistricts * HDwt[h]\n",
    "plt.hist(unitUse,weights=unitPop)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "id": "81a441d0-3a2f-473d-ba3b-0c8b365dfb55",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(unitPop,unitUse)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "id": "8b83001c-8544-4670-bfd2-3c47268f0967",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for u in range(nUnits):\n",
    "    if unitUse[u] < 0.4:\n",
    "        plotPoly(unitGeom[u])\n",
    "        plotCenter(u,unitGeom[u])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "id": "30de9de6-e831-4cfa-a449-2cc7bf3d330f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "classify these muni HDs by contiguity\n",
      "quick classification: who has contiguity problems?\n",
      "working on HD 0 time is now 0\n",
      "working on HD 700 time is now 73\n",
      "working on HD 1402 time is now 128\n",
      "working on HD 2102 time is now 166\n",
      "working on HD 2802 time is now 222\n",
      "working on HD 3503 time is now 263\n",
      "working on HD 4204 time is now 296\n",
      "working on HD 4906 time is now 356\n",
      "working on HD 5606 time is now 413\n",
      "working on HD 6306 time is now 471\n",
      "working on HD 7006 time is now 535\n",
      "working on HD 7706 time is now 610\n",
      "working on HD 8407 time is now 664\n",
      "out of 8934 total HDs, there were 8934.0 contiguous and 4039.0 complement-contiguous HDs\n",
      "0 HDs had both discontiguity problems, while enclave-only = 4895 and discontig only= 0\n",
      "here are the histograms of the small piece and enclave list lengths, total no = 0 4895\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "And here are the small-HD-piece and small-enclave pops\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"classify these muni HDs by contiguity\") #take from vanillaHD\n",
    "\n",
    "### THIS IS THE \"FIND DISCO\" CODE\n",
    "print(\"quick classification: who has contiguity problems?\")\n",
    "nUnbroken, nNoEnclave, smallPieceLists, enclaveLists, sPgenerator, eLgenerator = 0., 0., list(), list(), list(), list()\n",
    "smallPieceLengths, enclaveLengths = list(), list()\n",
    "doubleTroubleList = list()\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%700 == 0:\n",
    "        print(\"working on HD\",t,\"time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs,4) #,6) #6 is high (slow) to try to avoid false enclaves\n",
    "    if unbroken:\n",
    "        nUnbroken +=1\n",
    "    if noEnclave:\n",
    "        nNoEnclave +=1\n",
    "    if not unbroken:\n",
    "        smallPieceLists.append(smallPieceList)\n",
    "        smallPieceLengths.append(len(smallPieceList))\n",
    "        sPgenerator.append(t)\n",
    "    if not noEnclave and unbroken:   #district is contiguous but contains 1+ enclave\n",
    "        enclaveLists.append(enclaveList)\n",
    "        enclaveLengths.append(len(enclaveList))\n",
    "        eLgenerator.append(t)\n",
    "    if not noEnclave and not unbroken:  #extremely discontig (\"broken\") HDs can appear to have enclaves;\n",
    "        doubleTroubleList.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",nUnbroken,\"contiguous and\",nNoEnclave,\"complement-contiguous HDs\")\n",
    "print(len(doubleTroubleList),\"HDs had both discontiguity problems, while enclave-only =\",len(eLgenerator),\n",
    "      \"and discontig only=\",len(sPgenerator)-len(doubleTroubleList) )\n",
    "\n",
    "print(\"here are the histograms of the small piece and enclave list lengths, total no =\",\n",
    "      len(smallPieceLists),len(enclaveLists) )\n",
    "plt.hist([s for s in smallPieceLengths],label=\"small piece l units\",histtype='step',\n",
    "         cumulative=True,bins=[0,1,2,3,4,5,6,8,10,12,15,20,25,30,35,40,45,50,60,80,120])\n",
    "plt.hist([e for e in enclaveLengths],label=\"enclave l units\",histtype='step',\n",
    "         cumulative=True,bins=[0,1,2,3,4,5,6,8,10,12,15,20,25,30,35,40,45,50,60,80,120])\n",
    "plt.legend()\n",
    "plt.show()\n",
    "print(\"And here are the small-HD-piece and small-enclave pops\")\n",
    "plt.hist([sum(unitPop[u] for u in s) for s in smallPieceLists],label=\"small piece 1 pop\",histtype='step')\n",
    "plt.hist([sum(unitPop[u] for u in e) for e in enclaveLists],label=\"enclave 1 pop\",histtype='step')\n",
    "plt.legend()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "id": "6421f8ab-a699-4c29-976e-8c8e39d4597a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, let's fill in all enclaves that won't put us over 1022618 district pop vs 786629 target\n",
      "working on enclave-y HD 0 . We have evaluated 0 of 4895 enclavy HDs.Time is now 0\n",
      "working on enclave-y HD 375 . We have evaluated 200 of 4895 enclavy HDs.Time is now 11\n",
      "working on enclave-y HD 669 . We have evaluated 400 of 4895 enclavy HDs.Time is now 24\n",
      "working on enclave-y HD 904 . We have evaluated 600 of 4895 enclavy HDs.Time is now 36\n",
      "working on enclave-y HD 1255 . We have evaluated 800 of 4895 enclavy HDs.Time is now 46\n",
      "working on enclave-y HD 1619 . We have evaluated 1000 of 4895 enclavy HDs.Time is now 51\n",
      "working on enclave-y HD 1954 . We have evaluated 1200 of 4895 enclavy HDs.Time is now 58\n",
      "working on enclave-y HD 2278 . We have evaluated 1400 of 4895 enclavy HDs.Time is now 70\n",
      "working on enclave-y HD 2675 . We have evaluated 1600 of 4895 enclavy HDs.Time is now 81\n",
      "working on enclave-y HD 3048 . We have evaluated 1800 of 4895 enclavy HDs.Time is now 92\n",
      "working on enclave-y HD 3435 . We have evaluated 2000 of 4895 enclavy HDs.Time is now 98\n",
      "working on enclave-y HD 3846 . We have evaluated 2200 of 4895 enclavy HDs.Time is now 106\n",
      "working on enclave-y HD 4203 . We have evaluated 2400 of 4895 enclavy HDs.Time is now 113\n",
      "working on enclave-y HD 4525 . We have evaluated 2600 of 4895 enclavy HDs.Time is now 123\n",
      "working on enclave-y HD 4913 . We have evaluated 2800 of 4895 enclavy HDs.Time is now 136\n",
      "working on enclave-y HD 5362 . We have evaluated 3000 of 4895 enclavy HDs.Time is now 149\n",
      "working on enclave-y HD 5756 . We have evaluated 3200 of 4895 enclavy HDs.Time is now 163\n",
      "working on enclave-y HD 6166 . We have evaluated 3400 of 4895 enclavy HDs.Time is now 174\n",
      "working on enclave-y HD 6567 . We have evaluated 3600 of 4895 enclavy HDs.Time is now 184\n",
      "working on enclave-y HD 6859 . We have evaluated 3800 of 4895 enclavy HDs.Time is now 195\n",
      "working on enclave-y HD 7194 . We have evaluated 4000 of 4895 enclavy HDs.Time is now 212\n",
      "working on enclave-y HD 7515 . We have evaluated 4200 of 4895 enclavy HDs.Time is now 226\n",
      "working on enclave-y HD 7882 . We have evaluated 4400 of 4895 enclavy HDs.Time is now 237\n",
      "working on enclave-y HD 8315 . We have evaluated 4600 of 4895 enclavy HDs.Time is now 250\n",
      "working on enclave-y HD 8714 . We have evaluated 4800 of 4895 enclavy HDs.Time is now 261\n",
      "Out of 4895 HDs with enclaves 4895 had enclaves.\n",
      "Of these, 4876 wouldn't be over 1022618 if all enclaves filled, while 19 were too populous\n",
      "here is enclave pop by final pop for those we filled\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#copy enclave fix here.  Will not have any muni-discontig\n",
    "### THIS IS THE \"CANFILL\" CODE  #check if sum of enclave pops small enough to add\n",
    "maxNudgeUpPop = int(0.02 * aDP)\n",
    "maxPostFixPop = int(1.1 * aDP) #wider tolerance here for munis vs. vtd-based  ##note: was 1.3 when run, but should be 1.1\n",
    "print(\"Now, let's fill in all enclaves that won't put us over\",int(maxPostFixPop),\"district pop vs\",int(aDP),\"target\")\n",
    "nOrigEnclaves = [0 for t in range(nHDs)]\n",
    "totalEnclavePop = [0. for t in range(nHDs)]\n",
    "tryToFill, canFill, cantFill = list(), list(), list()\n",
    "startTime = time.time()  #takes about xx sec per HD triage\n",
    "        \n",
    "for iii, t in enumerate(eLgenerator):\n",
    "    if iii%200 == 0:\n",
    "        print(\"working on enclave-y HD\",t,\". We have evaluated\",iii,\"of\",len(eLgenerator),\"enclavy HDs.Time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if unbroken and not noEnclave:  #\"and unbroken\" new 1/15 - discontig HDs will usually appear to have enclaves.  We'll fix these in later block\n",
    "        tryToFill.append(t)\n",
    "        enclaveLists = getEnclaveLists(HDunitList[t], unitNbrs)\n",
    "        nOrigEnclaves[t] = len(enclaveLists)\n",
    "        totalEnclavePop[t] = np.sum( [ [np.sum([unitPop[u] for u in eL])] for eL in enclaveLists ] ) \n",
    "        if HDvPop[t] + totalEnclavePop[t] <= maxPostFixPop or totalEnclavePop[t] < maxNudgeUpPop:\n",
    "            canFill.append(t)\n",
    "            for eL in enclaveLists:\n",
    "                HDunitList[t] += eL\n",
    "                HDvPop[t] += np.sum([unitPop[u] for u in eL])\n",
    "        else:\n",
    "            cantFill.append(t)\n",
    "print(\"Out of\",len(eLgenerator),\"HDs with enclaves\",len(tryToFill),\"had enclaves.\")\n",
    "print(\"Of these,\",len(canFill),\"wouldn't be over\",maxPostFixPop,\"if all enclaves filled, while\",len(cantFill),\"were too populous\")\n",
    "plt.scatter([HDvPop[t] for t in canFill],[totalEnclavePop[t] for t in canFill])\n",
    "print(\"here is enclave pop by final pop for those we filled\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "id": "aced004d-abcf-4b9d-8249-332156a1759a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "defining and displaying current unit use after above manipulations; compare to original farther above.\n",
      "current avg use and its sd are 0.99518 0.06249\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"defining and displaying current unit use after above manipulations; compare to original farther above.\")\n",
    "HDweight = HDwt.copy()\n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += nDistricts * HDweight[t]\n",
    "activeUnitDistro, activeUnitWeights = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > 0.01:\n",
    "        activeUnitDistro.append(unitUse[u])\n",
    "        activeUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(activeUnitDistro, weights=activeUnitWeights, bins = 20, histtype = \"step\")\n",
    "#plt.show()\n",
    "currAvg, currSD = getWeightedAvgAndSD(activeUnitDistro, activeUnitWeights)\n",
    "print(\"current avg use and its sd are\",r5(currAvg),r5(currSD) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "id": "c06c0980-fad8-4596-bf2f-ad46bd6bb074",
   "metadata": {},
   "outputs": [],
   "source": [
    "savedHDunitList = [HDunitList[t].copy() for t in range(nHDs) ]  #safekeeping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "id": "80050c17-7680-4ea9-b803-dfc5bc057e5e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#savedHDunitList = [HDunitList[t].copy() for t in range(nHDs) ]  #safekeeping\n",
    "HDunitList = [savedHDunitList[t].copy() for t in range(nHDs) ]   #restart\n",
    "HDvPop = [0 for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "plt.axvline(aDP, ls=\"--\")\n",
    "plt.axvline(minDistrictPop, ls=\"dotted\")\n",
    "plt.axvline(maxDistrictPop, ls=\"dotted\")\n",
    "plt.hist([HDvPop[t] for t in popHDlist],bins=20)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "id": "827b8496-d66d-40ae-9780-a20243a54f92",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here are the HD centers for 19 cantFill HDs with border or big enclaves\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"here are the HD centers for\",len(cantFill),\"cantFill HDs with border or big enclaves\")\n",
    "for u in borderUnits:\n",
    "    plotPoly(unitGeom[u],0.1)\n",
    "for t in cantFill:\n",
    "    plotPoly(HDCP[t].buffer(0.02))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "id": "d4eec53d-e431-4e8d-a430-31ef4d1aa8c7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on avg unit-to-HDcp dist for HD 0\n",
      "working on avg unit-to-HDcp dist for HD 800\n",
      "working on avg unit-to-HDcp dist for HD 1602\n",
      "working on avg unit-to-HDcp dist for HD 2402\n",
      "working on avg unit-to-HDcp dist for HD 3203\n",
      "working on avg unit-to-HDcp dist for HD 4004\n",
      "working on avg unit-to-HDcp dist for HD 4806\n",
      "working on avg unit-to-HDcp dist for HD 5606\n",
      "working on avg unit-to-HDcp dist for HD 6406\n",
      "working on avg unit-to-HDcp dist for HD 7206\n",
      "working on avg unit-to-HDcp dist for HD 8006\n",
      "working on avg unit-to-HDcp dist for HD 8807\n",
      "all unit-toHDcp distances computed\n"
     ]
    }
   ],
   "source": [
    "barredJettisonSet = set([]) #for basic muni snap, there are no special corner units to freeze\n",
    "avgDist = [0. for t in range(nHDs)]  #about 6sec per 1000 HDs\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%800 == 0:\n",
    "        print(\"working on avg unit-to-HDcp dist for HD\",t)\n",
    "    avgDist[t] =  np.sum([unitPop[u]*unitCP[u].distance(hdCP[t]) for u in HDunitList[t] ]) / HDvPop[t]\n",
    "print(\"all unit-toHDcp distances computed\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "id": "76225203-dcf1-4845-b6a2-3b75e3749b01",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "for this code, all units are munis, not corner clusters\n",
      "remember, there are 0 units that are district-sized\n"
     ]
    }
   ],
   "source": [
    "print(\"for this code, all units are munis, not corner clusters\")\n",
    "allUnits = [u for u in range(nUnits)]\n",
    "wholeSet = set()\n",
    "for u in range(nUnits):\n",
    "    if unitPop[u] > minDistrictPop and unitPop[u] <= maxDistrictPop :\n",
    "        wholeSet.add(u)\n",
    "print(\"remember, there are\",len(wholeSet),\"units that are district-sized\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "id": "e3230001-cd19-4802-bd4d-c4590bdb0f3c",
   "metadata": {},
   "outputs": [],
   "source": [
    "badDiscoList = cantFill.copy() #sPgenerator + eLgenerator #cantFill.copy() #sPgenerator.copy()  #prep for below\n",
    "CCBgeom = list()  #no CCBgeoms in this ipynb\n",
    "#HDpoly = HDvtdGeom.copy()  #as shortcut, did not generate these shapes for the COI conversion code\n",
    "vtdArea = [tractGeom[v].area for v in range(nVTDs) ]\n",
    "HDarea = [np.sum([vtdArea[v] for v in HDvtdList[t] ]) for t in range(nHDs) ]\n",
    "HDcircle = [HDCP[t].buffer(0.23456*HDarea[t]**0.5) for t in range(nHDs) ] #approximation\n",
    "HDdiam = [HDarea[h] for h in range(nHDs)]\n",
    "maxGap = max(maxDistrictPop - aDP, 0.9 * np.median(unitPop) ) # = 0.05 * aDP\n",
    "HDnAddedUnits = [list() for h in range(nHDs)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "id": "187137f1-1009-49a1-8b46-715cc49e0ba8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "since these are running fast and MUSTFREE was kludgy in previous codes (possibly due to bad borderU assigns ...\n",
      ", go straight to MUSTSPAWN code - swelling\n",
      "And now, the major Disco's  Redraw fully using HDswell\n",
      "Assuming we have run the previous canSwell block.  This block repeats the code, but starting from the home unit\n",
      "This takes 1 - 1000 sec per HD :-( The total number of HDs to fix is 19\n",
      "swell-generating HD 12 our 1 th HD we must regrow out of 19 0 sec elapsed\n",
      "swell-generating HD 603 our 11 th HD we must regrow out of 19 5 sec elapsed\n"
     ]
    }
   ],
   "source": [
    "print(\"since these are running fast and MUSTFREE was kludgy in previous codes (possibly due to bad borderU assigns ...\")\n",
    "print(\", go straight to MUSTSPAWN code - swelling\")\n",
    "\n",
    "#THIS IS THE MUSTSPAWN code block - stolen from vanillaHD-OHredo\n",
    "print(\"And now, the major Disco's  Redraw fully using HDswell\")\n",
    "print(\"Assuming we have run the previous canSwell block.  This block repeats the code, but starting from the home unit\")\n",
    "print(\"This takes 1 - 1000 sec per HD :-( The total number of HDs to fix is\",len(badDiscoList))\n",
    "#avgDiam = MAP.area**0.5 / float(nDistricts)\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(badDiscoList):\n",
    "    if i%10 == 0:\n",
    "        print(\"swell-generating HD\",t,\"our\",i+1,\"th HD we must regrow out of\",len(badDiscoList),int(time.time()-startTime),\"sec elapsed\" )\n",
    "    notInCluster = True\n",
    "    for jj, geo in enumerate(CCBgeom):  #swell in-corner HDs from the corner cluster\n",
    "        if geo.contains(hdCP[t]):\n",
    "            starterU = allUnits.index(jj+0.25)\n",
    "            notInCluster = False\n",
    "    if notInCluster:\n",
    "        starterU = homeU[t]\n",
    "        #distList = [hdCP[t].distance(unitCP[u]) for u in HDunitList[t] ]\n",
    "        #starterU = HDunitList[t][distList.index(np.min(distList))]  #starter = unit with centroid closest to the hd center\n",
    "    contigUs = [starterU]  #we used getContigFromStarter(starterU, HDvtdList[t], unitNbrs) in above code block\n",
    "    contigPop = np.sum( [ unitPop[u] for u in contigUs ] )\n",
    "    gap = aDP - contigPop\n",
    "    origGap = gap\n",
    "    currList, addedList = contigUs.copy(), list()\n",
    "    adjoiners = list( set( getAdjoiners(currList, unitNbrs) ).difference(wholeSet) )\n",
    "    nearHDlist = [uu for uu in adjoiners]  #bias toward underused, close to HD (and its center)\n",
    "    #                                            subbed HDcircle for HDpoly in below\n",
    "    nearHDscore = [ (0.2*(unitUse[uu] - 1.) ) + 0.5*(unitCP[uu].distance(HDcircle[t]) + \n",
    "        unitCP[uu].distance(hdCP[t])  )  / HDdiam[t] for uu in adjoiners ]\n",
    "    stillGoing = True\n",
    "    \n",
    "    while gap > maxGap and len(nearHDlist) > 0 and stillGoing:   #add the lowest-scoring neighboring underused unit until we've roughly squared the HDpop\n",
    "        idx, i, notYetPicked = np.argsort(nearHDscore), 0, True\n",
    "        while i < len(nearHDscore) and notYetPicked:        \n",
    "            listNo = idx[i]   #nearHDscore.index(np.min(nearHDscore))\n",
    "            unitNoToAdd = nearHDlist[listNo]  #add this unit ...\n",
    "            canAdd  = wontEnclave(unitNoToAdd, currList, unitNbrs, borderUnits)\n",
    "            if canAdd:\n",
    "                notYetPicked = False\n",
    "            else:\n",
    "                i +=1\n",
    "        if notYetPicked:\n",
    "            stillGoing = False  #can't add any more units without creating an enclave\n",
    "        else: #we selected the best unit to add legally\n",
    "            gap -= unitPop[unitNoToAdd]\n",
    "            addedList.append(unitNoToAdd)\n",
    "            currList.append( unitNoToAdd)\n",
    "            for uu in unitNbrs[unitNoToAdd]: # ... and add its nonHD, nonwhole neighbors to future candidates\n",
    "                if uu not in currList and uu not in nearHDlist and unitPop[uu] < gap + maxGap and uu not in wholeSet:  \n",
    "                    nearHDlist.append(uu)                           #subbed HDcircle for HDpoly in below\n",
    "                    nearHDscore.append((0.1*(unitUse[uu] - 1.) ) + 0.5*(unitCP[uu].distance(HDcircle[t]) + \n",
    "                                                                        unitCP[uu].distance(hdCP[t])  )  / HDdiam[t] )\n",
    "            del nearHDscore[nearHDlist.index(unitNoToAdd)]        \n",
    "            del nearHDlist[ nearHDlist.index(unitNoToAdd) ]\n",
    "            for i, uu in enumerate(nearHDlist.copy()):\n",
    "                if unitPop[uu] > gap + maxGap:   #with the added pop from another unit, this unit is now too big to add\n",
    "                    del nearHDscore[nearHDlist.index(uu)]\n",
    "                    del nearHDlist[ nearHDlist.index(uu)]\n",
    "    for u in addedList:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "    for u in list( set(HDunitList[t]).difference(set(contigUs)) ):\n",
    "        unitUse[u] -= HDweight[t] * nDistricts       \n",
    "    HDunitList[t] = contigUs + addedList\n",
    "    HDvPop[t]    = np.sum( [unitPop[u] for u in HDunitList[t] ] )\n",
    "    HDnAddedUnits[t] = len(addedList)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3c7d49e2-454f-492d-9d7f-ed28598f59da",
   "metadata": {},
   "outputs": [],
   "source": [
    "#THIS IS THE MUSTFREE CODE - for high-pop HDs with map-border enclaves, can't fill; \n",
    "#   skipped; see another code for how this runs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "id": "597a6d42-0310-4544-b7ce-543a90d09dca",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "classify updated muni HDs by contiguity\n",
      "quick classification: who has contiguity problems?\n",
      "working on HD 0 time is now 0\n",
      "working on HD 700 time is now 6\n",
      "working on HD 1402 time is now 11\n",
      "working on HD 2102 time is now 16\n",
      "working on HD 2802 time is now 22\n",
      "working on HD 3503 time is now 27\n",
      "working on HD 4204 time is now 32\n",
      "working on HD 4906 time is now 40\n",
      "working on HD 5606 time is now 48\n",
      "working on HD 6306 time is now 55\n",
      "working on HD 7006 time is now 63\n",
      "working on HD 7706 time is now 73\n",
      "working on HD 8407 time is now 80\n",
      "out of 8934 total HDs, there were 8934.0 contiguous and 8934.0 complement-contiguous HDs\n",
      "0 HDs had both discontiguity problems, while enclave-only = 0 and discontig only= 0\n"
     ]
    }
   ],
   "source": [
    "print(\"classify updated muni HDs by contiguity\") #take from vanillaHD\n",
    "\n",
    "### THIS IS THE \"FIND DISCO\" CODE\n",
    "print(\"quick classification: who has contiguity problems?\")\n",
    "nUnbroken, nNoEnclave, smallPieceLists, enclaveLists, sPgenerator, eLgenerator = 0., 0., list(), list(), list(), list()\n",
    "smallPieceLengths, enclaveLengths = list(), list()\n",
    "doubleTroubleList = list()\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%700 == 0:\n",
    "        print(\"working on HD\",t,\"time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs,4) #,6) #6 is high (slow) to try to avoid false enclaves\n",
    "    if unbroken:\n",
    "        nUnbroken +=1\n",
    "    if noEnclave:\n",
    "        nNoEnclave +=1\n",
    "    if not unbroken:\n",
    "        smallPieceLists.append(smallPieceList)\n",
    "        smallPieceLengths.append(len(smallPieceList))\n",
    "        sPgenerator.append(t)\n",
    "    if not noEnclave and unbroken:   #district is contiguous but contains 1+ enclave\n",
    "        enclaveLists.append(enclaveList)\n",
    "        enclaveLengths.append(len(enclaveList))\n",
    "        eLgenerator.append(t)\n",
    "    if not noEnclave and not unbroken:  #extremely discontig (\"broken\") HDs can appear to have enclaves;\n",
    "        doubleTroubleList.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",nUnbroken,\"contiguous and\",nNoEnclave,\"complement-contiguous HDs\")\n",
    "print(len(doubleTroubleList),\"HDs had both discontiguity problems, while enclave-only =\",len(eLgenerator),\n",
    "      \"and discontig only=\",len(sPgenerator)-len(doubleTroubleList) )\n",
    "\n",
    "if len(smallPieceLists) + len(enclaveLists) > 0:\n",
    "    print(\"here are the histograms of the small piece and enclave list lengths, total no =\",\n",
    "          len(smallPieceLists),len(enclaveLists) )\n",
    "    plt.hist([s for s in smallPieceLengths],label=\"small piece l units\",histtype='step',\n",
    "             cumulative=True,bins=[0,1,2,3,4,5,6,8,10,12,15,20,25,30,35,40,45,50,60,80,120,200])\n",
    "    plt.hist([e for e in enclaveLengths],label=\"enclave l units\",histtype='step',\n",
    "             cumulative=True,bins=[0,1,2,3,4,5,6,8,10,12,15,20,25,30,35,40,45,50,60,80,120,200])\n",
    "    plt.legend()\n",
    "    plt.show()\n",
    "    print(\"And here are the small-HD-piece and small-enclave pops\")\n",
    "    plt.hist([sum(unitPop[u] for u in s) for s in smallPieceLists],label=\"small piece 1 pop\",histtype='step')\n",
    "    plt.hist([sum(unitPop[u] for u in e) for e in enclaveLists],label=\"enclave 1 pop\",histtype='step')\n",
    "    plt.legend()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "id": "d5ff711c-4bf6-437e-89fe-f30dda1a51a6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "let's visualize over-used and underused units, < 0.75 or > 1.25\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "and here is the histogram of HD pops\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "minUnitUse, maxUnitUse = 0.75, 1.25\n",
    "print(\"let's visualize over-used and underused units, <\",minUnitUse,\"or >\",maxUnitUse)\n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < minUnitUse:\n",
    "        plotPoly(unitGeom[u],0.4)\n",
    "        plotCenter(\"u\",unitCP[u])\n",
    "    if unitUse[u] > maxUnitUse:\n",
    "        plotPoly(unitGeom[u], 1.5)\n",
    "for c in range(nCounties):\n",
    "    plotPoly(countyGeom[c],0.1)\n",
    "plt.show()\n",
    "print(\"and here is the histogram of HD pops\")\n",
    "plt.hist([HDvPop[t] for t in popHDlist],bins = [0, 0.3*aDP, 0.45*aDP,0.6*aDP, 0.7*aDP, 0.85*aDP, 0.9*aDP, 0.95*aDP,\n",
    "         0.98*aDP, aDP, 1.02*aDP, 1.05*aDP, 1.1*aDP, 1.15*aDP, 1.3*aDP, 1.5*aDP, 2.0*aDP])\n",
    "plt.axvline(aDP,ls=\"--\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "id": "c2428bb3-f225-4e1f-aacb-abba4cc2cffb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "before rectifying pops, make another copy of the current HD lists\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pre-patch avg use and its sd are 0.99539 0.06015\n"
     ]
    }
   ],
   "source": [
    "print(\"before rectifying pops, make another copy of the current HD lists\")\n",
    "latestHDlist = [HDunitList[t].copy() for t in range(nHDs)]   #More safekeeping\n",
    "latestHDpop, latestUnitUse = [0. for t in range(nHDs)], [0. for u in range(nUnits)]\n",
    "for t in popHDlist:\n",
    "    for u in latestHDlist[t]:\n",
    "        latestHDpop[t] += unitPop[u]\n",
    "        latestUnitUse[u] += nDistricts * HDweight[t]\n",
    "latestUnitWeights, latestUnitDistro = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if latestUnitUse[u] > 0.1:\n",
    "        latestUnitDistro.append(latestUnitUse[u])\n",
    "        latestUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(latestUnitDistro, weights=latestUnitWeights, bins = 20, histtype = \"step\")\n",
    "plt.show()\n",
    "latestAvg, latestSD = getWeightedAvgAndSD(latestUnitDistro, latestUnitWeights)\n",
    "print(\"pre-patch avg use and its sd are\",r5(latestAvg),r5(latestSD) )"
   ]
  },
  {
   "cell_type": "raw",
   "id": "878bf68e-dbd9-4d98-9bae-efbdd132eb75",
   "metadata": {},
   "source": [
    "HDunitList = [latestHDlist[t].copy() for t in range(nHDs)] #restart\n",
    "HDvPop = [np.sum([unitPop[u] for u in HDunitList[t] ]) for t in range(nHDs) ]\n",
    "unitUse = [0.]*nUnits\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += nDistricts*HDweight[t]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "4fc22ecf-9460-43ef-a595-8a39026a9c39",
   "metadata": {},
   "outputs": [],
   "source": [
    "minDistrictPop, maxDistrictPop = 0.995 * aDP, 1.005 * aDP"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "id": "6b3dd3ff-706e-4e0d-a705-3a82cd62b519",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "We will now square up the 1524 HDs with pop < 782696 to within 3933\n",
      "working on squaring up HD 30 time is now 0\n",
      "working on squaring up HD 616 time is now 22\n",
      "working on squaring up HD 954 time is now 53\n",
      "working on squaring up HD 1148 time is now 92\n",
      "working on squaring up HD 1525 time is now 185\n",
      "working on squaring up HD 2624 time is now 217\n",
      "working on squaring up HD 3741 time is now 242\n",
      "working on squaring up HD 4111 time is now 275\n",
      "working on squaring up HD 4518 time is now 312\n",
      "working on squaring up HD 4836 time is now 346\n",
      "working on squaring up HD 5449 time is now 390\n",
      "working on squaring up HD 5855 time is now 457\n",
      "working on squaring up HD 7026 time is now 495\n",
      "working on squaring up HD 7892 time is now 610\n",
      "working on squaring up HD 8616 time is now 635\n",
      "working on squaring up HD 8869 time is now 674\n",
      "We have attempted to address underpop in a total of 1524 HDs\n",
      "Here is a scatterplot of original (x) to final pop (y)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#SQUARING UP UNDERPOPPED\n",
    "HDnAddedUnits, HDaddedPop = [0]*nHDs, [0.]*nHDs\n",
    "underPoppedList, stillUnderPoppedList = list(),list()\n",
    "#minDistrictPop, maxDistrictPop = 0.95 * aDP, 1.05 * aDP  #should have been previously defined\n",
    "for t,pop in enumerate(HDvPop):\n",
    "    if pop < minDistrictPop and t in popHDlist:\n",
    "        underPoppedList.append(t)\n",
    "maxGap = maxDistrictPop - aDP \n",
    "print(\"We will now square up the\",len(underPoppedList),\"HDs with pop <\",int(minDistrictPop),\"to within\",int(maxGap) )\n",
    "startTime = time.time()\n",
    "for ii,t in enumerate(underPoppedList):\n",
    "    if ii%100 == 0:\n",
    "        print(\"working on squaring up HD\",t,\"time is now\",int(time.time() - startTime)) \n",
    "    gap = aDP - HDvPop[t]\n",
    "    origGap = gap\n",
    "    nearHDlist, nearHDscore = list(), list()  #these will be dynamic lists of the nearby underused units\n",
    "    for u in HDunitList[t]:\n",
    "        for uu in unitNbrs[u]:\n",
    "            if uu not in HDunitList[t] and uu not in nearHDlist and unitPop[uu] < gap + maxGap:\n",
    "                nearHDlist.append(uu)   #below line: bias toward close, underused\n",
    "                nearHDscore.append((unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] )  \n",
    "    currList = HDunitList[t].copy()\n",
    "    addedList = list()\n",
    "    stillGoing = True\n",
    "    while gap > maxGap and len(nearHDlist) > 0 and stillGoing:   #add the lowest-scoring neighboring underused unit until we've roughly squared the HDpop\n",
    "        idx, i, notYetPicked = np.argsort(nearHDscore), 0, True\n",
    "        while i < len(nearHDscore) and notYetPicked:        \n",
    "            listNo = idx[i]   #nearHDscore.index(np.min(nearHDscore))\n",
    "            unitNoToAdd = nearHDlist[listNo]  #add this unit ...\n",
    "            canAdd  = wontEnclave(unitNoToAdd, currList, unitNbrs, borderUnits)\n",
    "            if canAdd: \n",
    "                notYetPicked = False\n",
    "            else:\n",
    "                i +=1\n",
    "        if notYetPicked:\n",
    "            stillGoing = False  #can't add any more units without creating an enclave\n",
    "        else:\n",
    "            gap -= unitPop[unitNoToAdd]\n",
    "            addedList.append(unitNoToAdd)\n",
    "            currList.append( unitNoToAdd)\n",
    "            for uu in unitNbrs[unitNoToAdd]:             # ... and add its nonHD neighbors to future candidates\n",
    "                if uu not in currList and uu not in nearHDlist and unitPop[uu] < gap + maxGap:  \n",
    "                    nearHDlist.append(uu)\n",
    "                    nearHDscore.append((unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] )  #bias toward close, underused\n",
    "            del nearHDscore[nearHDlist.index(unitNoToAdd)]        \n",
    "            del nearHDlist[ nearHDlist.index(unitNoToAdd) ]\n",
    "            for i, uu in enumerate(nearHDlist.copy()):\n",
    "                if unitPop[uu] > gap + maxGap:   #with the added pop from another unit, this unit is now too big to add\n",
    "                    del nearHDscore[nearHDlist.index(uu)]\n",
    "                    del nearHDlist[ nearHDlist.index(uu)]\n",
    "    for u in addedList:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "    HDunitList[t] += addedList\n",
    "    HDvPop[t]    = np.sum( [unitPop[u] for u in HDunitList[t] ] )\n",
    "    HDnAddedUnits[t] = len(addedList)\n",
    "    HDaddedPop[t] = np.sum( [unitPop[u] for u in addedList] )\n",
    "    if HDvPop[t] > maxDistrictPop:\n",
    "        print(\"Oops! HD\",t,\"now has overshot pop =\",int(HDvPop[t]),\"not\",int(aDP),\"after adding\",HDaddedPop[t] )\n",
    "    if HDvPop[t] < minDistrictPop:\n",
    "        stillUnderPoppedList.append(t)\n",
    "print(\"We have attempted to address underpop in a total of\",len(underPoppedList),\"HDs\")\n",
    "if len(stillUnderPoppedList) > 0:\n",
    "    print(\"... but we got stuck in\",len(stillUnderPoppedList))\n",
    "print(\"Here is a scatterplot of original (x) to final pop (y)\")\n",
    "plt.scatter([HDvPop[t] - HDaddedPop[t] for t in underPoppedList], [HDvPop[t] for t in underPoppedList])\n",
    "plt.plot([minDistrictPop,maxDistrictPop,maxDistrictPop,minDistrictPop],[minDistrictPop,minDistrictPop,maxDistrictPop,maxDistrictPop],lw=2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "id": "72398364-3e4a-4a03-a2cf-58a21bdea412",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "previous unit avg and sd usage are 0.99539 0.06015\n",
      "amped unit avg and sd usage are 1.00677 0.06223\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "prevUnitUse = [0.]*nUnits\n",
    "for t in popHDlist:\n",
    "    for u in latestHDlist[t]:\n",
    "        prevUnitUse[u] += HDweight[t] * nDistricts\n",
    "\n",
    "ampedUnitUse = [0. for u in range(nUnits)]\n",
    "ampedHDlist = [HDunitList[t].copy() for t in range(nHDs)]\n",
    "ampedHDpop = [HDvPop[t] for t in range(nHDs) ]\n",
    "for t in popHDlist:\n",
    "    for u in ampedHDlist[t]:\n",
    "        ampedUnitUse[u] += HDweight[t] * nDistricts   #KISS - recalc these\n",
    "plt.hist(prevUnitUse,bins=50,weights=unitPop,label=\"previous\",histtype=\"step\")\n",
    "plt.hist(ampedUnitUse, bins=50, weights=unitPop,label=\"amped\",histtype=\"step\")\n",
    "plt.legend()\n",
    "ampedUnitUseAvg, ampedUnitUseSD = getWeightedAvgAndSD(ampedUnitUse,unitPop)\n",
    "print(\"previous unit avg and sd usage are\",r5(latestAvg), r5(latestSD) )\n",
    "print(\"amped unit avg and sd usage are\",r5(ampedUnitUseAvg), r5(ampedUnitUseSD) )\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "id": "f703cd30-fc17-4e4e-a458-40d9c74b266b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Continuing with narrowing the distro.  This loop: remove overused units from overpopped HDs\n",
      "Let's now square down the 2539 overPopped HDs to within 3933\n",
      "working on squaring down HD 3 time is now 0\n",
      "working on squaring down HD 724 time is now 23\n",
      "working on squaring down HD 1467 time is now 42\n",
      "working on squaring down HD 2001 time is now 80\n",
      "working on squaring down HD 2753 time is now 111\n",
      "working on squaring down HD 3288 time is now 141\n",
      "working on squaring down HD 4081 time is now 157\n",
      "working on squaring down HD 4672 time is now 171\n",
      "working on squaring down HD 5469 time is now 197\n",
      "working on squaring down HD 6269 time is now 217\n",
      "working on squaring down HD 6964 time is now 242\n",
      "working on squaring down HD 7575 time is now 261\n",
      "working on squaring down HD 8390 time is now 285\n",
      "We have attempted to address overpop in a total of 2539 HDs\n",
      "Here is a scatterplot of original to final pop\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#SQUARING DOWN\n",
    "print(\"Continuing with narrowing the distro.  This loop: remove overused units from overpopped HDs\")\n",
    "HDnShedUnits = [0]*nHDs\n",
    "overPoppedList, stillOverPoppedList = list(), list()\n",
    "startTime = time.time()\n",
    "for t,pop in enumerate(HDvPop):\n",
    "    if pop > maxDistrictPop and t in popHDlist:\n",
    "        overPoppedList.append(t)\n",
    "\n",
    "maxGap = aDP - minDistrictPop   \n",
    "print(\"Let's now square down the\",len(overPoppedList),\"overPopped HDs to within\", int(maxGap))   \n",
    "for ii,t in enumerate(overPoppedList):\n",
    "    if ii%200 == 0:\n",
    "        print(\"working on squaring down HD\",t,\"time is now\",int(time.time()-startTime))\n",
    "    unbroken, noEnclave, sPL, ePL = enclaveCheck(HDunitList[t],unitNbrs)\n",
    "    if not (unbroken and noEnclave):\n",
    "        print(\"SKIPPING shedding attempt on overpopped HD\",t,\"with pop\",HDvPop[t],\"because it was not legal to start\")\n",
    "    else:\n",
    "        excess = HDvPop[t] - aDP\n",
    "        origExcess = excess\n",
    "        HDboundaryList, HDboundaryScore = list(), list()  #these will be dynamic lists of the overused border units to jettison\n",
    "        #distList = [hdCP[t].distance(unitCP[u]) for u in HDunitList[t] ]\n",
    "        starterU = homeU[t] #HDunitList[t][distList.index(np.min(distList))] #update from vanillaHD\n",
    "        barredSet = barredJettisonSet.union({starterU})\n",
    "        for u in set(HDunitList[t]).difference(barredSet):\n",
    "            isBoundary = False\n",
    "            for uu in unitNbrs[u]:\n",
    "                if uu not in HDunitList[t]:\n",
    "                    isBoundary = True\n",
    "                    break\n",
    "            if isBoundary and HDvPop[t] - unitPop[u] > aDP - maxGap:  #shedding this unit won't send us too far under targetpop\n",
    "                HDboundaryList.append(u)\n",
    "                HDboundaryScore.append((1. - unitUse[u]) - unitCP[u].distance(hdCP[t]) / avgDist[t])  #low-score = bias toward far, overused\n",
    "        currList = HDunitList[t].copy()\n",
    "        shedList, stillGoing = list(), True\n",
    "        while excess > maxGap and len(HDboundaryList) > 0 and stillGoing:   #shed the highest-scoring neighboring overused unit until we've roughly squared the HDpop\n",
    "            idx, i, notYetPicked = np.argsort(HDboundaryScore), 0, True\n",
    "            while i < len(HDboundaryScore) and notYetPicked and stillGoing:        \n",
    "                listNo = idx[i]   #low (large negative) score is preferred to shed\n",
    "                unitNoToShed = HDboundaryList[listNo]  # attempt to shed this unit ...\n",
    "                tryList = list(set(currList).difference( {unitNoToShed} ) )\n",
    "                unbroken, noEnclave, sPL, ePL = enclaveCheck(tryList,unitNbrs) \n",
    "                if unbroken and noEnclave:             #... if that won't eff up contiguity\n",
    "                    notYetPicked = False\n",
    "                else:\n",
    "                    i +=1\n",
    "            if notYetPicked:\n",
    "                stillGoing = False  #can't drop any more units without creating an enclave\n",
    "                print(\"can't drop any more units to HD\",t,\"without creating an enclave\")\n",
    "            else: #add this eligible unit\n",
    "                shedList.append(unitNoToShed)\n",
    "                excess -= unitPop[unitNoToShed]        \n",
    "                del currList[currList.index(unitNoToShed) ]\n",
    "                del HDboundaryList[listNo]\n",
    "                del HDboundaryScore[listNo]\n",
    "                for u in unitNbrs[unitNoToShed]:      # ... and ID any neighboring units that will now be on boundary after we shed this unit\n",
    "                    if u in currList and u not in HDboundaryList and (unitPop[u] <= excess + maxGap and u not in barredSet): \n",
    "                        HDboundaryList.append(u)\n",
    "                        HDboundaryScore.append( (1. - unitUse[u]) - unitCP[u].distance(hdCP[t]) / avgDist[t] )  #low-score, bias toward far & overused       \n",
    "                for uu in HDboundaryList.copy():\n",
    "                    if unitPop[uu] > excess + maxGap:  #checking to see if the latest pop change DQ's any large units on current boundary\n",
    "                        del HDboundaryScore[HDboundaryList.index(uu)]\n",
    "                        del HDboundaryList[HDboundaryList.index(uu)]   \n",
    "        for u in shedList:\n",
    "            unitUse[u] -= HDweight[t] * nDistricts\n",
    "        HDunitList[t], HDvPop[t] = currList.copy(), np.sum( [unitPop[u] for u in currList ] )    \n",
    "        if HDvPop[t] < minDistrictPop:\n",
    "            print(\"Oops! HD\",t,\"now has undershot pop =\",int(HDvPop[t]),\"not\",int(aDP),\"after shedding\",\n",
    "                 np.sum([unitPop[u] for u in shedList]) )        \n",
    "        if HDvPop[t] > maxDistrictPop:\n",
    "            stillOverPoppedList.append(t)\n",
    "        HDnShedUnits[t] = -1 * len(shedList)\n",
    "        if homeU[t] not in HDunitList[t]:\n",
    "            print(\"WARNING: we lost the home unit\",homeU[t],\"from HD\",HD)\n",
    "            lostHomeUlist.append(t)\n",
    "            \n",
    "print(\"We have attempted to address overpop in a total of\",len(overPoppedList),\"HDs\")\n",
    "if len(stillOverPoppedList) > 0:\n",
    "    print(\"... but we got stuck in\",len(stillOverPoppedList))\n",
    "print(\"Here is a scatterplot of original to final pop\")\n",
    "plt.scatter([ampedHDpop[t] for t in overPoppedList], [HDvPop[t] for t in overPoppedList])\n",
    "plt.axvline(aDP, 0.9*aDP, 1.1*aDP, ls=\"--\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "id": "9c4d12b3-8596-4a5b-937e-7ef8ed71a903",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "updating our unitUse, underpopped and overpopped lists\n",
      "unit use histogram\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trimmed unit avg and sd usage are 1.00003 0.06113\n",
      "unit use by pop\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "we now have a total of 0 underpopped HDs and 0 overpopped HDs\n"
     ]
    }
   ],
   "source": [
    "print(\"updating our unitUse, underpopped and overpopped lists\")\n",
    "unitUse = [0.]*nUnits\n",
    "HDvPop = [0.]*nHDs\n",
    "stillUnder, stillOver = list(), list()\n",
    "for t in popHDlist:\n",
    "    if homeU[t] not in HDunitList[t]:\n",
    "        print(\"WARNING - we lost home unit\",homeU[t],\"from HD\",t)\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += nDistricts * HDweight[t]\n",
    "        HDvPop[t] += unitPop[u]\n",
    "    if HDvPop[t] < minDistrictPop:\n",
    "        stillUnder.append(t)\n",
    "    if HDvPop[t] > maxDistrictPop:\n",
    "        stillOver.append(t)\n",
    "print(\"unit use histogram\")\n",
    "plt.hist(unitUse, weights = unitPop)\n",
    "plt.show()\n",
    "trimmedUnitUseAvg, trimmedUnitUseSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "print(\"trimmed unit avg and sd usage are\",r5(trimmedUnitUseAvg), r5(trimmedUnitUseSD) )\n",
    "print(\"unit use by pop\")\n",
    "plt.scatter(unitPop,unitUse)\n",
    "plt.show()\n",
    "print(\"we now have a total of\",len(stillUnder),\"underpopped HDs and\",len(stillOver),\"overpopped HDs\")\n"
   ]
  },
  {
   "cell_type": "raw",
   "id": "08544911-9783-4491-9da2-87a52ad4ad5f",
   "metadata": {},
   "source": [
    "plt.hist([unitPop[homeU[t]] for t in stillUnder],histtype =\"step\",label=\"underPopped\")\n",
    "plt.hist([unitPop[homeU[t]] for t in stillOver],histtype =\"step\",label=\"overPopped\")\n",
    "plt.xlabel(\"homeU pop\")\n",
    "plt.legend()\n",
    "plt.axvline(aDP,ls=\"--\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "raw",
   "id": "caa3baed-db33-4c9d-8230-fee56fd1429e",
   "metadata": {},
   "source": [
    "print(\"here are centerpoints of under (small circles) and overpopped (faint shape) HDs\")\n",
    "for t in stillOver:\n",
    "    plotPoly(HDCP[t].buffer(0.03),0.5)\n",
    "for t in stillUnder:\n",
    "    plotPoly(HDCP[t].buffer(0.01),1)\n",
    "for c in range(nCounties):\n",
    "    plotPoly(countyGeom[c],0.1)\n",
    "#for u in range(nUnits):\n",
    "#    if unitUse[u] > 1.2 :\n",
    "#        plotPoly(unitGeom[u],0.5)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "80237be0-91bd-444b-84ad-fa8f4abad76e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "these appear scattered.  Try assigning same list as for nearest VTD in same muni or county\n",
      "updating our unitUse, underpopped and overpopped lists\n",
      "WARNING - we lost home unit 862 from HD 2337\n",
      "unit use histogram\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "unit use by pop\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "we now have a total of 0 underpopped HDs and 0 overpopped HDs\n"
     ]
    }
   ],
   "source": [
    "print(\"these appear scattered.  Try assigning same list as for nearest VTD in same muni or county\")\n",
    "for v in stillUnder:\n",
    "    u = homeU[v]\n",
    "    goodList = list(set(unitTractList[u]).difference(set(stillUnder)))\n",
    "    if len(goodList) == 0: #muni is all bad, so expand list to county\n",
    "        goodList = list(set(countyTractList[countyNo[v]]).difference(set(stillUnder)) )\n",
    "    goodDist = [tractCP[v].distance(tractCP[vv]) for vv in goodList]\n",
    "    goodV = goodList[goodDist.index(np.min(goodDist))]\n",
    "    HDunitList[v] = HDunitList[goodV].copy()\n",
    "\n",
    "print(\"updating our unitUse, underpopped and overpopped lists\")\n",
    "unitUse = [0.]*nUnits\n",
    "HDvPop = [0.]*nHDs\n",
    "stillUnder, stillOver = list(), list()\n",
    "for t in popHDlist:\n",
    "    if homeU[t] not in HDunitList[t]:\n",
    "        print(\"WARNING - we lost home unit\",homeU[t],\"from HD\",t)\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += nDistricts * HDweight[t]\n",
    "        HDvPop[t] += unitPop[u]\n",
    "    if HDvPop[t] < minDistrictPop:\n",
    "        stillUnder.append(t)\n",
    "    if HDvPop[t] > maxDistrictPop:\n",
    "        stillOver.append(t)\n",
    "print(\"unit use histogram\")\n",
    "plt.hist(unitUse, weights = unitPop)\n",
    "plt.show()\n",
    "print(\"unit use by pop\")\n",
    "plt.scatter(unitPop,unitUse)\n",
    "plt.show()\n",
    "print(\"we now have a total of\",len(stillUnder),\"underpopped HDs and\",len(stillOver),\"overpopped HDs\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "id": "38c2661c-3a1e-4c8f-8a0f-e1c0a1ca1e32",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "quick classification: who has contiguity problems?\n",
      "working on HD 0 time is now 0\n",
      "working on HD 700 time is now 6\n",
      "working on HD 1402 time is now 12\n",
      "working on HD 2102 time is now 17\n",
      "working on HD 2802 time is now 23\n",
      "working on HD 3503 time is now 28\n",
      "working on HD 4204 time is now 33\n",
      "working on HD 4906 time is now 40\n",
      "working on HD 5606 time is now 48\n",
      "working on HD 6306 time is now 56\n",
      "working on HD 7006 time is now 64\n",
      "working on HD 7706 time is now 74\n",
      "working on HD 8407 time is now 80\n",
      "out of 8934 total HDs, there were 8934.0 contiguous and 8934.0 complement-contiguous HDs\n",
      "0 HDs had both discontiguity problems, while enclave-only = 0 and discontig only= 0\n"
     ]
    }
   ],
   "source": [
    "\n",
    "print(\"quick classification: who has contiguity problems?\")\n",
    "nUnbroken, nNoEnclave, smallPieceLists, enclaveLists, sPgenerator, eLgenerator = 0., 0., list(), list(), list(), list()\n",
    "smallPieceLengths, enclaveLengths = list(), list()\n",
    "doubleTroubleList = list()\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%700 == 0:\n",
    "        print(\"working on HD\",t,\"time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs,4) #,6) #6 is high (slow) to try to avoid false enclaves\n",
    "    if unbroken:\n",
    "        nUnbroken +=1\n",
    "    if noEnclave:\n",
    "        nNoEnclave +=1\n",
    "    if not unbroken:\n",
    "        smallPieceLists.append(smallPieceList)\n",
    "        smallPieceLengths.append(len(smallPieceList))\n",
    "        sPgenerator.append(t)\n",
    "    if not noEnclave and unbroken:   #district is contiguous but contains 1+ enclave\n",
    "        enclaveLists.append(enclaveList)\n",
    "        enclaveLengths.append(len(enclaveList))\n",
    "        eLgenerator.append(t)\n",
    "    if not noEnclave and not unbroken:  #extremely discontig (\"broken\") HDs can appear to have enclaves;\n",
    "        doubleTroubleList.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",nUnbroken,\"contiguous and\",nNoEnclave,\"complement-contiguous HDs\")\n",
    "print(len(doubleTroubleList),\"HDs had both discontiguity problems, while enclave-only =\",len(eLgenerator),\n",
    "      \"and discontig only=\",len(sPgenerator)-len(doubleTroubleList) )\n",
    "\n",
    "if len(smallPieceLists) + len(enclaveLists) > 0:\n",
    "    print(\"here are the histograms of the small piece and enclave list lengths, total no =\",\n",
    "          len(smallPieceLists),len(enclaveLists) )\n",
    "    plt.hist([s for s in smallPieceLengths],label=\"small piece l units\",histtype='step',\n",
    "             cumulative=True,bins=[0,1,2,3,4,5,6,8,10,12,15,20,25,30,35,40,45,50,60,80,120,200])\n",
    "    plt.hist([e for e in enclaveLengths],label=\"enclave l units\",histtype='step',\n",
    "             cumulative=True,bins=[0,1,2,3,4,5,6,8,10,12,15,20,25,30,35,40,45,50,60,80,120,200])\n",
    "    plt.legend()\n",
    "    plt.show()\n",
    "    print(\"And here are the small-HD-piece and small-enclave pops\")\n",
    "    plt.hist([sum(unitPop[u] for u in s) for s in smallPieceLists],label=\"small piece 1 pop\",histtype='step')\n",
    "    plt.hist([sum(unitPop[u] for u in e) for e in enclaveLists],label=\"enclave 1 pop\",histtype='step')\n",
    "    plt.legend()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "id": "37944660-9197-4e58-ac32-0a2bdad79616",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.005000000000000038\n"
     ]
    }
   ],
   "source": [
    "print(maxGap/aDP)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "id": "703d18f8-eccb-411f-b295-e66405ca328c",
   "metadata": {},
   "outputs": [],
   "source": [
    "saved2unitList = [HDunitList[t].copy() for t in range(nHDs)] #safekeeping\n",
    "#HDunitList = [saved2unitList[t].copy() for t in range(nHDs)] #restart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "id": "9c07f7b4-cff5-4964-a792-bf80d474444f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "min, max uses are 0.68250904618569 1.3831308040846786\n"
     ]
    }
   ],
   "source": [
    "HDunitList = [saved2unitList[t].copy() for t in range(nHDs)] #restart\n",
    "HDvPop = [np.sum([unitPop[u] for u in HDunitList[t] ]) for t in range(nHDs) ]\n",
    "unitUse = [0.]*nUnits\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += nDistricts * HDweight[t]\n",
    "print(\"min, max uses are\",np.min(unitUse),np.max(unitUse) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "id": "7dbe8d70-907e-4b4a-a42e-9fa60d4d7cd0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "current relative pop.  Total number of stillOver = 0\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist([HDvPop[t]/aDP for t in popHDlist],bins=40)\n",
    "plt.axvline(minDistrictPop/aDP,ls=\"--\")\n",
    "plt.axvline(maxDistrictPop/aDP,ls=\"--\")\n",
    "print(\"current relative pop.  Total number of stillOver =\",len(stillOver))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "id": "145e1646-9fa6-44dc-8be5-d3832c91025b",
   "metadata": {},
   "outputs": [],
   "source": [
    "for t in popHDlist:\n",
    "    if homeU[t] not in HDunitList[t]:\n",
    "        print(t,\"lost its home U\",homeU[t],\"with pop\",unitPop[homeU[t]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "id": "12192a10-cd2d-4a08-8ef5-468827329a01",
   "metadata": {},
   "outputs": [],
   "source": [
    "#see OH_schoolSnap99 for additional triage options; not needed here"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "id": "a90790d8-6f94-419b-8d88-d7476194c185",
   "metadata": {},
   "outputs": [],
   "source": [
    "splitUnitNo, splitUnitFrac, hasSplitUnit = [-999]*nHDs, [0.]*nHDs, [0]*nHDs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "id": "add6b13f-f45c-498e-82f3-c8778d0dc65e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "interm save in HDunitList format\n"
     ]
    }
   ],
   "source": [
    "print(\"interm save in HDunitList format\")\n",
    "tList = [t for t in range(nHDs)]\n",
    "outDF = pd.DataFrame( {\"vtd\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDunitList\":HDunitList,\n",
    "                      \"splitUnitNo\":splitUnitNo,\"splitUnitFrac\":splitUnitFrac,\n",
    "                       \"centroid x\":HDCPx, \"centroid y\":HDCPy, \"homeU\":homeU, \"homeC\":countyNo } )\n",
    "outname = STATE+str(int(nHDs))+\"_\"+str(nDistricts)+\"_5cityReady2Patch.csv\" \n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "id": "382c7962-d3dd-4fd0-b3b8-51f8b6e7eb2b",
   "metadata": {},
   "outputs": [],
   "source": [
    "failedList = list() #not neded in school15; all HDs are groovy\n",
    "prePatchedList = [HDunitList[t].copy() for t in range(nHDs)] #safekeeping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "id": "e5bba0ce-dc4a-494e-86b3-0fbefed0e032",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For now, we will freeze the HDs with split units or block-forced prior to patching.\n",
      "Start with underpatching. This algorithm simplified vs. vanillaHD to manage blockiness.\n",
      "Currently, we will stop patching when the overall sd of usage is less than 0.046\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter updated maxSD value 0.046\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this would currently cover a total of 942 units\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter updated number of units to try boosting usage 300\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are currently 1549 units out of 5683 with usage below 0.98\n",
      "maxExchangePop is currently 0.05 fraction of avgDistrictPop\n",
      "Let's further tighten the distro with exchanges up to 39331 = aDP* 0.05\n",
      "current avg and SD of unit usage are 1.00003 0.06113 . Now trying to increase up to 300 units' underusage\n",
      "all done trying2increase usage of unit 777 final usage = 0.98131 220 sec elapsed 172 0 complete, failed patches, unstarted= 20\n",
      "current avg and SD of usage are 1.00007 0.05954\n",
      "all done trying2increase usage of unit 692 final usage = 0.98001 411 sec elapsed 134 0 complete, failed patches, unstarted= 3\n",
      "current avg and SD of usage are 1.0001 0.05887\n",
      "all done trying2increase usage of unit 3037 final usage = 0.98181 771 sec elapsed 112 0 complete, failed patches, unstarted= 2\n",
      "current avg and SD of usage are 1.00014 0.05822\n",
      "all done trying2increase usage of unit 2911 final usage = 0.89218 868 sec elapsed 65 0 complete, failed patches, unstarted= 101\n",
      "current avg and SD of usage are 1.00015 0.05737\n",
      "all done trying2increase usage of unit 1559 final usage = 0.9165 982 sec elapsed 90 0 complete, failed patches, unstarted= 34\n",
      "current avg and SD of usage are 1.00017 0.05658\n",
      "all done trying2increase usage of unit 1934 final usage = 0.98156 1271 sec elapsed 91 0 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 1.00018 0.05574\n",
      "all done trying2increase usage of unit 348 final usage = 0.96896 1388 sec elapsed 90 0 complete, failed patches, unstarted= 21\n",
      "current avg and SD of usage are 1.00022 0.05481\n",
      "all done trying2increase usage of unit 3651 final usage = 0.98153 1499 sec elapsed 94 0 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 1.00026 0.05433\n",
      "all done trying2increase usage of unit 420 final usage = 0.92645 1664 sec elapsed 81 0 complete, failed patches, unstarted= 3\n",
      "current avg and SD of usage are 1.00025 0.0539\n",
      "begin usage increase for unit 4727 with usage 0.82273 . Sec, total UU units tried = 1666 10\n",
      "all done trying2increase usage of unit 4727 final usage = 0.98013 1778 sec elapsed 95 0 complete, failed patches, unstarted= 2\n",
      "current avg and SD of usage are 1.00026 0.05348\n",
      "all done trying2increase usage of unit 4021 final usage = 0.95976 1921 sec elapsed 74 0 complete, failed patches, unstarted= 30\n",
      "current avg and SD of usage are 1.00027 0.05295\n",
      "all done trying2increase usage of unit 1735 final usage = 0.98116 1993 sec elapsed 87 0 complete, failed patches, unstarted= 118\n",
      "current avg and SD of usage are 1.00029 0.05201\n",
      "all done trying2increase usage of unit 2933 final usage = 0.98127 2121 sec elapsed 92 0 complete, failed patches, unstarted= 30\n",
      "current avg and SD of usage are 1.0003 0.05122\n",
      "all done trying2increase usage of unit 1674 final usage = 0.98141 2302 sec elapsed 95 0 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 1.00034 0.05077\n",
      "all done trying2increase usage of unit 4014 final usage = 0.98028 2456 sec elapsed 79 0 complete, failed patches, unstarted= 29\n",
      "current avg and SD of usage are 1.00034 0.05025\n",
      "all done trying2increase usage of unit 741 final usage = 0.97672 2555 sec elapsed 82 0 complete, failed patches, unstarted= 87\n",
      "current avg and SD of usage are 1.00036 0.04959\n",
      "all done trying2increase usage of unit 4725 final usage = 0.97505 2726 sec elapsed 85 0 complete, failed patches, unstarted= 64\n",
      "current avg and SD of usage are 1.00037 0.04907\n",
      "all done trying2increase usage of unit 610 final usage = 0.97215 2897 sec elapsed 96 0 complete, failed patches, unstarted= 77\n",
      "current avg and SD of usage are 1.00038 0.04854\n",
      "all done trying2increase usage of unit 1123 final usage = 0.95508 3146 sec elapsed 79 0 complete, failed patches, unstarted= 4\n",
      "current avg and SD of usage are 1.00039 0.04813\n",
      "begin usage increase for unit 1902 with usage 0.85342 . Sec, total UU units tried = 3148 20\n",
      "all done trying2increase usage of unit 1902 final usage = 0.98319 3413 sec elapsed 66 0 complete, failed patches, unstarted= 5\n",
      "current avg and SD of usage are 1.00039 0.04765\n",
      "all done trying2increase usage of unit 1122 final usage = 0.96733 3769 sec elapsed 85 0 complete, failed patches, unstarted= 35\n",
      "current avg and SD of usage are 1.00039 0.04747\n",
      "all done trying2increase usage of unit 64 final usage = 0.98036 3936 sec elapsed 76 0 complete, failed patches, unstarted= 51\n",
      "current avg and SD of usage are 1.00039 0.04707\n",
      "all done trying2increase usage of unit 1657 final usage = 0.98055 3999 sec elapsed 60 0 complete, failed patches, unstarted= 54\n",
      "current avg and SD of usage are 1.00041 0.04647\n",
      "all done trying2increase usage of unit 61 final usage = 0.98046 4169 sec elapsed 76 0 complete, failed patches, unstarted= 79\n",
      "current avg and SD of usage are 1.00041 0.04607\n",
      "all done trying2increase usage of unit 3677 final usage = 0.98129 4303 sec elapsed 66 0 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 1.00042 0.04595\n"
     ]
    }
   ],
   "source": [
    "print(\"For now, we will freeze the HDs with split units or block-forced prior to patching.\")\n",
    "print(\"Start with underpatching. This algorithm simplified vs. vanillaHD to manage blockiness.\")\n",
    "\n",
    "maxSD = 0.046  #0.07  #0.05   #adjust down if distro already tight, adjust up if blocky\n",
    "print(\"Currently, we will stop patching when the overall sd of usage is less than\",maxSD)\n",
    "maxSD = float(input(\"enter updated maxSD value\"))\n",
    "stopMinUse = 1. - maxSD\n",
    "#print(\"we will stop patching on individual underused units when their usage exceeds\",r5(stopMinUse))\n",
    "maxNtries = 0\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < stopMinUse:\n",
    "        maxNtries +=1\n",
    "print(\"this would currently cover a total of\",maxNtries,\"units\")\n",
    "maxNtries = int(input(\"enter updated number of units to try boosting usage\"))\n",
    "stopMinUse = 0.98 #float(input(\"enter updated stopMinUse value for ending usage boost on a unit; I reco 0.98\"))\n",
    "nInPlay = 0\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < stopMinUse:\n",
    "        nInPlay +=1\n",
    "print(\"there are currently\",nInPlay,\"units out of\",nUnits,\"with usage below\",stopMinUse)\n",
    "maxExchangePop = 0.05*aDP #for 5city, no need to widen vs. vanillaHD; not blocky\n",
    "print(\"maxExchangePop is currently\",r5(maxExchangePop/aDP),\"fraction of avgDistrictPop\")\n",
    "debug1 = 10 #int(input(\"enter 1 to print out stats for every patched HD, otherwise enter reporting frequency\"))\n",
    "print(\"Let's further tighten the distro with exchanges up to\",int(maxExchangePop),\"= aDP*\",r3(maxExchangePop/aDP) ) \n",
    "maxGap = aDP - minDistrictPop #0.9 * np.median(unitPop) \n",
    "currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "nonfrozenList = list()  \n",
    "for t in popHDlist:\n",
    "    if hasSplitUnit[t] != 1 and t not in failedList:  #don't mess with the small number of HDs that had major challenges\n",
    "        nonfrozenList.append(t)\n",
    "\n",
    "attemptedSmallUs, startTime = list(), time.time()\n",
    "print(\"current avg and SD of unit usage are\",r5(currAvg), r5(currSD),\". Now trying to increase up to\",maxNtries,\"units' underusage\" )\n",
    "startTime = time.time()\n",
    "while currSD > maxSD and len(attemptedSmallUs) < maxNtries:\n",
    "    #simplified vs. vanillaHD - always work on the lowest-used unit.\n",
    "    eligUnitUse = unitUse.copy()\n",
    "    for u in range(nUnits):\n",
    "        if u in attemptedSmallUs: #we already tried this one, so lock it out\n",
    "            eligUnitUse[u] = 999.  #preventing re-selection\n",
    "    UUU = eligUnitUse.index(np.min(eligUnitUse))\n",
    "    attemptedSmallUs.append(UUU)\n",
    "    UUUc = [UUU] + unitNbrs[UUU]\n",
    "    if len(attemptedSmallUs) % debug1 == 0:\n",
    "        print(\"begin usage increase for unit\",UUU,\"with usage\",r5(unitUse[UUU]),\". Sec, total UU units tried =\",\n",
    "              int(time.time()-startTime),len(attemptedSmallUs) )\n",
    "    for u in UUUc.copy():\n",
    "        if unitUse[u] > 1.:\n",
    "            UUUc.remove(u)  #...drop any overused neighbors of the primary UUU from the target sheddable cluster\n",
    "    uuuHDs, uuuDists, UUUcSet = list(), list(), set(UUUc)\n",
    "    for t in nonfrozenList: #popHDlist:  #finding all HDs with at least one cluster member on the boundary\n",
    "        if UUU not in HDunitList[t]:\n",
    "            HDadjoinSet = set( getAdjoiners(HDunitList[t],unitNbrs) )\n",
    "            if len(HDadjoinSet.intersection(UUUcSet) ) > 0: #the UUU or one of its underused 1-neighbors adjoins this HD\n",
    "                uuuHDs.append(t)  #Note: we'll check later if we can contiguously pick up the UUU's cluster\n",
    "                uuuDists.append( unitCP[UUU].distance(hdCP[t]) / avgDist[t] )\n",
    "        idx0 = np.argsort(uuuDists)\n",
    "    hasCandidates = True\n",
    "    if len(uuuDists) == 0:  #this underused unit is buried inside others; skip it\n",
    "        hasCandidates = False\n",
    "        print(\"   Couldn't find any HDs adjacent to underused unit\",UUU)\n",
    "    nPatchSuccess, nPatchFail, nCouldntStart, idxNo = 0,0,0,-1\n",
    "    while unitUse[UUU] < stopMinUse and idxNo < 0.8*len(uuuHDs) and hasCandidates: #arbitrarily only examine 80% closest of HDs\n",
    "        excess, giveUpOnShedding = 99*aDP, True  #default = failed swap\n",
    "        idxNo += 1\n",
    "        if idxNo % 40 == 0 and debug1 == 1:\n",
    "            print(\"try to add unit\",UUU,\"from\",abs(idxNo),\"th HD.  Usage up to\",unitUse[UUU] )\n",
    "        t = uuuHDs[idx0[idxNo]]\n",
    "        trySet = set(HDunitList[t]).union(UUUcSet)\n",
    "        contig,complementContig, __, ___ = enclaveCheck(list(trySet), unitNbrs)\n",
    "        loopUUUc = UUUc.copy()  #default; we will add whole cluster\n",
    "        if not (contig and complementContig): #we can't add whole cluster; neighbors may be enclavy.   Try just adding the UUU\n",
    "            trySet = set(HDunitList[t]).union({UUU})\n",
    "            contig,complementContig, __, ___ = enclaveCheck(list(trySet), unitNbrs)\n",
    "            loopUUUc = [UUU]\n",
    "        if contig and complementContig:  #we can at least add the cluster, let's go for more\n",
    "            HDuuuSet = set(loopUUUc).difference(set(HDunitList[t]))  #the subset of the UUU cluster that adjoins (NOT in) this HD\n",
    "            HDuuuCpop = np.sum([unitPop[u] for u in HDuuuSet])\n",
    "            giveUpOnAdding = False            \n",
    "            addCandidates, addUseDists = list(), list()\n",
    "            uuCandidates = getAdjoiners(trySet, unitNbrs)  #any adjoiner can be picked up, even if far from UUUc\n",
    "            for u in uuCandidates:\n",
    "                if HDuuuCpop + unitPop[u] <= maxExchangePop:\n",
    "                    addCandidates.append(u)  #Below's relative scoring of use and distance is a bit arbitrary\n",
    "                    addUseDists.append((unitUse[uu]-1.) + 0.1*unitCP[uu].distance(hdCP[t]) / avgDist[t])  #bias toward close, underused\n",
    "            if len(addCandidates) == 0:\n",
    "                giveUpOnAdding = True\n",
    "            while HDuuuCpop < maxExchangePop and not giveUpOnAdding:\n",
    "                addNneighbors = [len( set(unitNbrs[addC]).intersection(trySet) ) for addC in addCandidates ]\n",
    "                addScores = addUseDists.copy()\n",
    "                for jjj, u in enumerate(addCandidates):\n",
    "                    if addNneighbors[jjj] == 1:\n",
    "                        addScores[jjj] += 0.4321    #discourage growing fingers\n",
    "                #print(\"HDuuuCpop is now\",HDuuuCpop)\n",
    "                idx, ij, notYetPicked = np.argsort(addScores), 0, True\n",
    "                while ij < 0.5*len(addScores) and notYetPicked:\n",
    "                    listNo = idx[ij]   #work from low to high score\n",
    "                    addU = addCandidates[listNo]\n",
    "                    cContig = wontEnclave(addU, list(trySet), unitNbrs, borderUnits)  #4/20/24 sub this in as faster? vs below line\n",
    "                    #contig,cContig, __, ___ = enclaveCheck(list(trySet.union({addU}) ), unitNbrs)  #4/20/24 this is unnec slow\n",
    "                    if cContig: #contig and cContig:\n",
    "                        notYetPicked = False\n",
    "                        HDuuuCpop += unitPop[addU]\n",
    "                        HDuuuSet.add(addU)\n",
    "                        trySet.add(addU)\n",
    "                        del addUseDists[addCandidates.index(addU)]\n",
    "                        del addCandidates[addCandidates.index(addU)]                        \n",
    "                        for uu in list(set(unitNbrs[addU]).difference(trySet) ): \n",
    "                            if uu not in addCandidates and unitPop[uu] + HDuuuCpop < maxExchangePop and unitUse[uu] < 1.01:\n",
    "                                addCandidates.append(uu)\n",
    "                                addUseDists.append( (unitUse[uu]-1.) + 0.1*unitCP[uu].distance(hdCP[t]) / avgDist[t] )\n",
    "                    else:\n",
    "                        ij +=1\n",
    "                if notYetPicked:\n",
    "                    giveUpOnAdding = True  #all candidates would create a discontig, so can't shed any more units\n",
    "            addSet = HDuuuSet.copy()  #we're done building the list of underused units to add to this HD\n",
    "            trySet = set(HDunitList[t]).union(addSet) \n",
    "            excess = np.sum([unitPop[u] for u in trySet]) - aDP\n",
    "            shedCandidates, shedScores, giveUpOnShedding = list(), list(), False\n",
    "            bdryCandidates = getBdryNonEdgers(trySet, unitNbrs)  #new - any boundary unit can be shed, even if far from OUUc\n",
    "            for u in bdryCandidates:\n",
    "                if unitPop[u] <= excess + maxGap and u != homeU[t]:\n",
    "                    shedCandidates.append(u)\n",
    "                    shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])  #bias toward OVERUSED, far\n",
    "            if len(shedCandidates) == 0:\n",
    "                giveUpOnShedding = True\n",
    "            shedSet = set()\n",
    "            while excess > maxGap and not giveUpOnShedding:\n",
    "                #print(\"excess pop is now\",excess,\"for HD\",t)\n",
    "                idx, ij, notYetPicked = np.argsort(shedScores), 0, True\n",
    "                while ij < len(shedScores) and notYetPicked:\n",
    "                    listNo = idx[-1-ij]   #work from high to low score\n",
    "                    shedU = shedCandidates[listNo]\n",
    "                    if shedScores[listNo] <= 0:  #we're delving into the underused; stop adding to shed list\n",
    "                        break\n",
    "                    if excess - unitPop[shedU] >= -1*maxGap:\n",
    "                        contig,cContig, __, ___ = enclaveCheck(list(trySet.difference({shedU}) ), unitNbrs)\n",
    "                        if contig and cContig:\n",
    "                            notYetPicked = False\n",
    "                            excess -= unitPop[shedU]\n",
    "                            trySet.remove(shedU)\n",
    "                            shedSet.add(shedU)\n",
    "                            del shedScores[shedCandidates.index(shedU)]\n",
    "                            del shedCandidates[shedCandidates.index(shedU)]\n",
    "                            newSheddables = set(unitNbrs[shedU]).intersection(trySet)\n",
    "                            for u in newSheddables:\n",
    "                                if excess - unitPop[u] >= -1*maxGap and u not in shedCandidates + [homeU[t]]:\n",
    "                                    shedCandidates.append(u)  #we'll check enclavity if ever picked\n",
    "                                    shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])\n",
    "                            for kkk, u in enumerate(shedCandidates): #checking if this shed eliminates high-pop future sheds ...\n",
    "                                if excess - unitPop[u] < -1*maxGap:\n",
    "                                    del shedScores[kkk]\n",
    "                                    del shedCandidates[kkk]\n",
    "                    ij +=1\n",
    "                if notYetPicked:\n",
    "                    giveUpOnShedding = True  #all shedcandidates would create a discontig, so can't shed enough units to square pop\n",
    "            legitSwap = False\n",
    "            currPop = np.sum([ unitPop[u] for u in trySet] )\n",
    "            if abs(currPop - aDP) <= maxGap: \n",
    "                contig,cContig, __, ___ = enclaveCheck(list(trySet), unitNbrs) \n",
    "                if contig and cContig:\n",
    "                    legitSwap = True\n",
    "            if legitSwap:\n",
    "                for u in shedSet:\n",
    "                    unitUse[u] -= HDweight[t] * nDistricts\n",
    "                for u in addSet:\n",
    "                    unitUse[u] += HDweight[t] * nDistricts\n",
    "                HDunitList[t] = list(trySet)\n",
    "                HDvPop[t] = np.sum([ unitPop[u] for u in HDunitList[t] ])\n",
    "                nPatchSuccess +=1\n",
    "                #print(\"we added\",addSet,\"and shed units\",shedSet,\"from HD\",t)\n",
    "            else:\n",
    "                nPatchFail +=1\n",
    "        else:  #adding neither the UUU cluster or just the UUU worked; couldn't even start\n",
    "            nCouldntStart +=1\n",
    "            # end of shed + add patching on this HD\n",
    "            #print(\"shed and patched for HD, OUU\",t,OUU)\n",
    "\n",
    "    print(\"all done trying2increase usage of unit\",UUU,\"final usage =\",r5(unitUse[UUU]),int(time.time()-startTime),\"sec elapsed\",\n",
    "         nPatchSuccess,nPatchFail,\"complete, failed patches, unstarted=\",nCouldntStart)\n",
    "    currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "    print(\"current avg and SD of usage are\",r5(currAvg), r5(currSD) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "id": "6f7f2f60-aa6c-4d46-b2e3-7d2f68841e68",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " patched use avg 1.00042 and SD 0.04595\n",
      "And here is the pop distro\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking contiguity of final HDs\n",
      "working on HD 0 out of 8941\n",
      "working on HD 800 out of 8941\n",
      "working on HD 1600 out of 8941\n",
      "working on HD 2400 out of 8941\n",
      "working on HD 3200 out of 8941\n",
      "working on HD 4000 out of 8941\n",
      "working on HD 4800 out of 8941\n",
      "working on HD 5600 out of 8941\n",
      "working on HD 6400 out of 8941\n",
      "working on HD 7200 out of 8941\n",
      "working on HD 8000 out of 8941\n",
      "working on HD 8800 out of 8941\n",
      "all done checking HD and complement contiguity for all 8941 HDs\n"
     ]
    }
   ],
   "source": [
    "patchedUse, unpUse = [0.]*nUnits, [0.]*nUnits\n",
    "for t in popHDlist:\n",
    "    if homeU[t] not in HDunitList[t]:\n",
    "        print(\"WARNING - we lost home unit\",homeU[t],\"from HD\",t)\n",
    "    for u in HDunitList[t]:\n",
    "        patchedUse[u] += HDweight[t] * nDistricts\n",
    "    if hasSplitUnit[t] == 1:\n",
    "        unitUse[splitUnitNo[t]] -= (1. - splitUnitFrac[t]) * nDistricts * HDweight[t]\n",
    "#    for u in unpatchedHDlist[t]:\n",
    "#        unpUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(patchedUse,bins=50, label=\"patched\",histtype=\"step\")\n",
    "#plt.hist(unpUse, bins=50, label=\"unpatched\",histtype=\"step\")\n",
    "plt.legend()\n",
    "plt.show()\n",
    "patchedAvg, patchedSD = getWeightedAvgAndSD(patchedUse,unitPop)\n",
    "#unpatchedAvg, unpatchedSD = getWeightedAvgAndSD(unpUse,unitPop)\n",
    "print(\" patched use avg\", r5(patchedAvg),\"and SD\",r5(patchedSD) )\n",
    "#print(\"unpatched, patched use avgs are\",r5(unpatchedAvg), r5(patchedAvg),\"and their SDs are\",r5(unpatchedSD), r5(patchedSD) )\n",
    "print(\"And here is the pop distro\")\n",
    "plt.hist([HDvPop[t] for t in popHDlist])\n",
    "plt.axvline(aDP, ls=\"--\",color=\"orange\")\n",
    "plt.axvline(minDistrictPop, ls=\"dotted\")\n",
    "plt.axvline(maxDistrictPop, ls=\"dotted\")\n",
    "plt.show()\n",
    "print(\"checking contiguity of final HDs\")\n",
    "for t in popHDlist:\n",
    "    if t%800 == 0:\n",
    "        print(\"working on HD\",t,\"out of\",nHDs)\n",
    "    unbroken, noEnclave, sList, eList = enclaveCheck(HDunitList[t], unitNbrs)  #these HDunitLists now appear to be sets\n",
    "    if not unbroken or not noEnclave:\n",
    "        print(\"uh-oh, HD\",t,\"has contiguity, complement-contiguity of\",unbroken, noEnclave)\n",
    "print(\"all done checking HD and complement contiguity for all\",nHDs,\"HDs\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "id": "3749959c-a557-4e14-9bab-e031e6fc9f62",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "interm save in HDunitList format\n"
     ]
    }
   ],
   "source": [
    "print(\"interm save in HDunitList format\")\n",
    "tList = [t for t in range(nHDs)]\n",
    "outDF = pd.DataFrame( {\"vtd\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDunitList\":HDunitList,\n",
    "                      \"splitUnitNo\":splitUnitNo,\"splitUnitFrac\":splitUnitFrac,\n",
    "                       \"centroid x\":HDCPx, \"centroid y\":HDCPy, \"homeU\":homeU, \"homeC\":countyNo } )\n",
    "outname = STATE+str(int(nHDs))+\"_\"+str(nDistricts)+\"_5cityUnderpatched045.csv\" \n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "id": "5faa4270-4a8f-4777-b514-6d72cd77718b",
   "metadata": {},
   "outputs": [],
   "source": [
    "underpatchedUnitList = [HDunitList[t].copy() for t in range(nHDs) ] #safekeeping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "id": "63ff3e3c-81f2-4f54-9a92-d07fdeb12cc0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "current avg and SD of usage are 1.00042 0.04595\n"
     ]
    }
   ],
   "source": [
    "HDunitList = [underpatchedUnitList[t].copy() for t in range(nHDs) ] #restart\n",
    "HDvPop = [np.sum([unitPop[u] for u in HDunitList[t]]) for t in range(nHDs)]\n",
    "unitUse = [0.]*nUnits\n",
    "for t in popHDlist:\n",
    "    if homeU[t] not in HDunitList[t]:\n",
    "        print(\"WARNING - we lost home unit\",homeU[t],\"from HD\",t)\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "    if hasSplitUnit[t] == 1:\n",
    "        unitUse[splitUnitNo[t]] -= (1. - splitUnitFrac[t]) * nDistricts * HDweight[t]\n",
    "\n",
    "\n",
    "currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "print(\"current avg and SD of usage are\",r5(currAvg), r5(currSD) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "id": "6e54e08e-d07a-418f-b730-7bbc9d336a23",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "we are still biased toward high overuse for large units, so do another round of overpatch\n",
      "0.04 = default maxSD. Reco'ing 0.05 for blocky, 0.08 when only partially underpatched before this\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter maxSD 0.04\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "default use threshold for moving on to next overused unit is 1.02\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter updated stopMaxUse value 1.02\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are currently 1930 units out of 5683 with usage above 1.02\n",
      "maxExchangePop is currently 0.1 fraction of avgDistrictPop\n",
      "this block reduces overuse, with exchanges up to 78662\n",
      "current avg and SD of unit usage are 1.00042 0.04595 . Now trying to reduce up to 1930 units' overusage\n",
      "starting to reduce usage for unit 454 with usage 1.25817 . Total units tried = 1\n",
      "try to drop unit 454 from 0 th HD out of 564 possible.  usage down to 1.2581698737089992\n",
      "try to drop unit 454 from 90 th HD out of 564 possible.  usage down to 1.1016871297705153\n",
      "all done trying to reduce usage of unit 454 final usage = 1.01932 678 sec elapsed 125 10 successful, failed patches, couldn't start= 2\n",
      "current avg and SD of usage are 1.00035 0.04398\n",
      "starting to reduce usage for unit 372 with usage 1.18065 . Total units tried = 2\n",
      "try to drop unit 372 from 0 th HD out of 701 possible.  usage down to 1.1806505694161091\n",
      "try to drop unit 372 from 90 th HD out of 701 possible.  usage down to 1.0359090526943486\n",
      "all done trying to reduce usage of unit 372 final usage = 1.01896 897 sec elapsed 102 3 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00028 0.04259\n",
      "starting to reduce usage for unit 531 with usage 1.11978 . Total units tried = 3\n",
      "try to drop unit 531 from 0 th HD out of 468 possible.  usage down to 1.1197845865328235\n",
      "all done trying to reduce usage of unit 531 final usage = 1.019 1104 sec elapsed 57 25 successful, failed patches, couldn't start= 7\n",
      "current avg and SD of usage are 1.00026 0.04119\n",
      "starting to reduce usage for unit 109 with usage 1.10235 . Total units tried = 4\n",
      "try to drop unit 109 from 0 th HD out of 436 possible.  usage down to 1.1023456351514458\n",
      "all done trying to reduce usage of unit 109 final usage = 1.0185 1184 sec elapsed 49 7 successful, failed patches, couldn't start= 34\n",
      "current avg and SD of usage are 1.00024 0.04004\n",
      "starting to reduce usage for unit 1127 with usage 1.08423 . Total units tried = 5\n",
      "try to drop unit 1127 from 0 th HD out of 461 possible.  usage down to 1.0842329234381038\n",
      "try to drop unit 1127 from 90 th HD out of 461 possible.  usage down to 1.032610169560141\n",
      "all done trying to reduce usage of unit 1127 final usage = 1.01786 1495 sec elapsed 41 71 successful, failed patches, couldn't start= 49\n",
      "current avg and SD of usage are 1.00023 0.03957\n"
     ]
    }
   ],
   "source": [
    "#SECOND PATCHING BLOCK -- OVERUSERS.  applies a suppression of LONG STRINGS.  \n",
    "print(\"we are still biased toward high overuse for large units, so do another round of overpatch\")\n",
    "#SECOND PATCHING BLOCK -- OVERUSERS.  applies a suppression of LONG STRINGS.  \n",
    "maxSD = 0.04 #0.06  #0.08  #0.04 \n",
    "print(maxSD,\"= default maxSD. Reco'ing 0.05 for blocky, 0.08 when only partially underpatched before this\")\n",
    "maxSD = float(input(\"enter maxSD\"))\n",
    "stopMaxUse = 1.02 #1.+  2.* maxSD  #0.5*maxSD  #don't be too aggressive; may create long chains\n",
    "print(\"default use threshold for moving on to next overused unit is\",r5(stopMaxUse) )\n",
    "stopMaxUse = float(input(\"enter updated stopMaxUse value\"))\n",
    "nInPlay = 0\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > stopMaxUse:\n",
    "        nInPlay +=1\n",
    "print(\"there are currently\",nInPlay,\"units out of\",nUnits,\"with usage above\",stopMaxUse)\n",
    "nBigUsers = 5\n",
    "maxExchangePop = 0.10*aDP  #0.15 or 0.25 is debatable.  use 0.15 unless blocky\n",
    "print(\"maxExchangePop is currently\",r5(maxExchangePop/aDP),\"fraction of avgDistrictPop\")\n",
    "print(\"this block reduces overuse, with exchanges up to\",int(maxExchangePop)) #\n",
    "maxGap = aDP - minDistrictPop  #0.9 * np.median(unitPop) # = aDP - minDistrictPop\n",
    "maxNtries = 0\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > stopMaxUse:\n",
    "        maxNtries +=1\n",
    "currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "nonfrozenList = list()\n",
    "for t in popHDlist:\n",
    "    if t not in hasSplitUnit: #hasSplitUnit[t] != 1:  #don't mess with the small number of HDs that have to have a split muni\n",
    "        nonfrozenList.append(t)\n",
    "        \n",
    "attemptedBigUs = list()\n",
    "print(\"current avg and SD of unit usage are\",r5(currAvg), r5(currSD),\". Now trying to reduce up to\",maxNtries,\"units' overusage\" )\n",
    "startTime = time.time()\n",
    "while currSD > maxSD and len(attemptedBigUs) < maxNtries: \n",
    "    #simplified vs. vanillaHD - just take the biggest overuser\n",
    "    eligUnitUse = unitUse.copy()\n",
    "    for u in range(nUnits):\n",
    "        if u in attemptedBigUs: #we already tried this one, so lock it out\n",
    "            eligUnitUse[u] = -999.  #preventing re-selection\n",
    "    OUU = eligUnitUse.index(np.max(eligUnitUse))\n",
    "    attemptedBigUs.append(OUU)  #so we don't try this unit again in a future loop\n",
    "    if unitPop[OUU] > 0.05 * aDP:  #some overusers are high-pop.  If so, will drop only this unit, not any neighbors\n",
    "        OUUc = [OUU]\n",
    "    else:\n",
    "        OUUc = [OUU] + unitNbrs[OUU]\n",
    "    print(\"starting to reduce usage for unit\",OUU,\"with usage\",r5(unitUse[OUU]),\". Total units tried =\",len(attemptedBigUs) )\n",
    "    for u in OUUc.copy():\n",
    "        if unitUse[u] < 1.:\n",
    "            OUUc.remove(u)  #...drop any underused neighbors of the primary OUU from the target sheddable cluster\n",
    "    OUUcSet = set( OUUc)  #for muni-snap, overused are isolated.  So don't bother adding two-level neighbors to cluster\n",
    "    ouuHDs, ouuDists = list(), list()\n",
    "    for t in nonfrozenList: #popHDlist:  #finding all HDs with at least one cluster member on the boundary\n",
    "        if OUU in HDunitList[t] and homeU[t] != OUU: #can't drop the home muni\n",
    "            HDadjoinSet =   set( getAdjoiners(HDunitList[t],unitNbrs) )\n",
    "            OUUcAdjoinSet = set( getAdjoiners(list(OUUcSet),unitNbrs) )\n",
    "            if len(HDadjoinSet.intersection(OUUcAdjoinSet) ) > 0: #the OUU or one of its overused 1-neighbors adjoins the complement\n",
    "                ouuHDs.append(t)  #so we can shed the OOUc to the complement\n",
    "                ouuDists.append( unitCP[OUU].distance(hdCP[t]) / avgDist[t] )\n",
    "    nPatchSuccess, nPatchFail, nCouldntStart, idxNo, idx0 = 0, 0, 0, 0, np.argsort(ouuDists)\n",
    "    while unitUse[OUU] > stopMaxUse and idxNo > -0.8*len(ouuHDs) : #arbitrarily only examine 80% of HDs, biasing farthest ones       \n",
    "        if idxNo % 90 == 0:\n",
    "            print(\"try to drop unit\",OUU,\"from\",abs(idxNo),\"th HD out of\",len(ouuHDs),\"possible.  usage down to\",unitUse[OUU] )\n",
    "        idxNo -=1\n",
    "        t = ouuHDs[idx0[idxNo]]\n",
    "        thisLoopOUUc = [OUU]\n",
    "        possibleOUUc = list((  OUUcSet.intersection(set(HDunitList[t]) )  ).difference( {homeU[t]} )) #again, homeU is untouchable\n",
    "        if np.sum([unitPop[u] for u in possibleOUUc]) < 0.05*aDP:\n",
    "            thisLoopOUUc = possibleOUUc.copy() #we can add the whole non-HDincluded cluster (-homeU) without exceeding 0.25 aDP            \n",
    "        trySet = set(HDunitList[t]).difference(set(thisLoopOUUc))\n",
    "        contig,complementContig, __, ___ = enclaveCheck(list(trySet), unitNbrs)\n",
    "        if not (contig and complementContig):  #dropping the cluster creates a problem (likely an HD discontig).  Try something simpler ...\n",
    "            if len(set(unitNbrs[OUU]).intersection(HDadjoinSet) )  > 0:  #Yay! The OUU itself on border.  Try dropping just it, not the full cluster\n",
    "                HDouuSet = {OUU}\n",
    "                trySet = set(HDunitList[t]).difference( {OUU} )\n",
    "                contig,complementContig, __, ___ = enclaveCheck(list(trySet), unitNbrs)\n",
    "        else:\n",
    "            HDouuSet = set(HDunitList[t]).intersection(set(thisLoopOUUc))  #set(OUUc)\n",
    "        if contig and complementContig:  #we can at least drop the cluster, let's go for more\n",
    "            #HDouuSet = set(HDunitList[t]).intersection(set(OUUc))  #the subset of the OUU cluster that's in this HD.  Defined above\n",
    "            HDouuCpop = np.sum([unitPop[u] for u in HDouuSet])\n",
    "            giveUpOnShedding = False            \n",
    "            shedCandidates, shedScores = list(), list()\n",
    "            bdryCandidates = getBdryNonEdgers(trySet, unitNbrs)  #new - any boundary unit can be shed, even if far from OUUc\n",
    "            for u in bdryCandidates:\n",
    "                if HDouuCpop + unitPop[u] <= maxExchangePop and u != homeU[t]:\n",
    "                    shedCandidates.append(u)\n",
    "                    shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])  #bias toward far, overused\n",
    "            if len(shedCandidates) == 0:\n",
    "                giveUpOnShedding = True\n",
    "            while HDouuCpop < maxExchangePop and not giveUpOnShedding:\n",
    "                idx, ij, notYetPicked = np.argsort(shedScores), 0, True\n",
    "                while ij < len(shedScores) and notYetPicked:\n",
    "                    listNo = idx[-1-ij]   #work from high to low score\n",
    "                    shedU = shedCandidates[listNo]\n",
    "                    if shedScores[listNo] <= 0:  #we're delving into the underused; stop adding to shed list\n",
    "                        break\n",
    "                    contig,cContig, __, ___ = enclaveCheck(list(trySet.difference({shedU}) ), unitNbrs)\n",
    "                    if contig and cContig:\n",
    "                        notYetPicked = False\n",
    "                        HDouuCpop += unitPop[shedU]\n",
    "                        #print(\"shedding unit\",shedU,\"from HD\",t,\"total shed Pop now\", HDouuCpop)\n",
    "                        HDouuSet.add(shedU)\n",
    "                        trySet.remove(shedU)\n",
    "                        del shedScores[shedCandidates.index(shedU)]\n",
    "                        del shedCandidates[shedCandidates.index(shedU)]\n",
    "                        newSheddables = set(unitNbrs[shedU]).intersection(trySet)\n",
    "                        for u in newSheddables:\n",
    "                            if HDouuCpop + unitPop[u] <= maxExchangePop and u not in shedCandidates and u != homeU[t]:\n",
    "                                shedCandidates.append(u)\n",
    "                                shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])\n",
    "                    else:\n",
    "                        ij +=1\n",
    "                if notYetPicked:\n",
    "                    giveUpOnShedding = True  #all candidates would create a discontig, so can't shed any more units\n",
    "            shedSet = HDouuSet.copy()  #set(OUUc).intersection(set(HDunitList[t]))\n",
    "            trySet = set(HDunitList[t]).difference(shedSet) \n",
    "            gap = aDP - np.sum([unitPop[u] for u in trySet])\n",
    "            nearHDlist, nearHDscore = list(), list()  #these will be dynamic lists of the nearby underused units\n",
    "            for u in trySet:\n",
    "                for uu in unitNbrs[u]:\n",
    "                    if uu not in HDunitList[t] and uu not in nearHDlist and unitPop[uu] < gap + maxGap and unitUse[uu] < 1.01:\n",
    "                        nearHDlist.append(uu)\n",
    "                        nearHDscore.append(5.*(unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] )\n",
    "                        #bias toward UNDERUSED, close\n",
    "            addedSet = set( )    \n",
    "            stillGoing = True \n",
    "            while gap > maxGap and len(nearHDlist) > 0 and stillGoing:   #add the lowest-scoring neighboring underused unit until we've roughly squared the HDpop\n",
    "                nearHDscore2 = nearHDscore.copy()\n",
    "                for ij, uu in enumerate(nearHDlist):\n",
    "                    nHDnbrs = len( set(unitNbrs[uu]).intersection(trySet) )\n",
    "                    if nHDnbrs == 1 :  #BIAS AGAINST CREATING A SLIM CHAIN\n",
    "                        nearHDscore2[ij] *= 0.5   #make this score closer to zero (less negative) \n",
    "                idx, ij, notYetPicked = np.argsort(nearHDscore2), 0, True   #originally, used nearHDscore itself here\n",
    "                while ij < len(nearHDscore) and notYetPicked:        \n",
    "                    listNo = idx[ij]   #nearHDscore.index(np.min(nearHDscore))\n",
    "                    unitNoToAdd = nearHDlist[listNo]  #add this unit ...                            \n",
    "                    canAdd  = wontEnclave(unitNoToAdd, list(trySet), unitNbrs, borderUnits)\n",
    "                    if canAdd:\n",
    "                        notYetPicked = False\n",
    "                    else:\n",
    "                        ij +=1\n",
    "                if notYetPicked:\n",
    "                    stillGoing = False  #can't add any more units; we can't without creating an enclave\n",
    "                else:\n",
    "                    gap -= unitPop[unitNoToAdd]\n",
    "                    addedSet.add(unitNoToAdd)\n",
    "                    trySet.add( unitNoToAdd)\n",
    "                    for uu in unitNbrs[unitNoToAdd]:             # ... and add its nonHD neighbors to future candidates\n",
    "                        if uu not in trySet and uu not in nearHDlist and unitPop[uu] < gap + maxGap and unitUse[uu] < 1.01:  \n",
    "                            nearHDlist.append(uu)\n",
    "                            nearHDscore.append(5.* (unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] ) \n",
    "                            #bias toward UNDERUSED, ~close\n",
    "                    del nearHDscore[nearHDlist.index(unitNoToAdd)]        \n",
    "                    del nearHDlist[ nearHDlist.index(unitNoToAdd) ]\n",
    "                    for ijj, uu in enumerate(nearHDlist.copy()):\n",
    "                        if unitPop[uu] > gap + maxGap:   #with the added pop from another unit, this unit is now too big to add\n",
    "                            del nearHDscore[nearHDlist.index(uu)]\n",
    "                            del nearHDlist[ nearHDlist.index(uu)]\n",
    "            currPop = np.sum([unitPop[u] for u in trySet])\n",
    "            if abs(currPop - aDP) <= maxGap:\n",
    "                for u in shedSet:\n",
    "                    unitUse[u] -= HDweight[t] * nDistricts\n",
    "                for u in addedSet:\n",
    "                    unitUse[u] += HDweight[t] * nDistricts\n",
    "                HDunitList[t] = list(trySet)\n",
    "                HDvPop[t]    = currPop\n",
    "                nPatchSuccess +=1\n",
    "            else:\n",
    "                nPatchFail +=1\n",
    "            # end of shed + add patching on this HD\n",
    "            #print(\"shed and patched for HD, OUU\",t,OUU)\n",
    "        else:\n",
    "            nCouldntStart +=1\n",
    "            #print(\"Due to discontiguity, can't drop OUU cluster for HD, OUU\", t, OUU)\n",
    "    print(\"all done trying to reduce usage of unit\",OUU,\"final usage =\",r5(unitUse[OUU]),int(time.time()-startTime),\"sec elapsed\",\n",
    "         nPatchSuccess,nPatchFail,\"successful, failed patches, couldn't start=\",nCouldntStart)\n",
    "    currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "    print(\"current avg and SD of usage are\",r5(currAvg), r5(currSD) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "id": "35140f52-2cb9-40e6-be15-ac02ba88316c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " patched use avg 1.00023 and SD 0.03957\n",
      "And here is the pop distro\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking contiguity of final HDs\n",
      "working on HD 0 out of 8941\n",
      "working on HD 800 out of 8941\n",
      "working on HD 1600 out of 8941\n",
      "working on HD 2400 out of 8941\n",
      "working on HD 3200 out of 8941\n",
      "working on HD 4000 out of 8941\n",
      "working on HD 4800 out of 8941\n",
      "working on HD 5600 out of 8941\n",
      "working on HD 6400 out of 8941\n",
      "working on HD 7200 out of 8941\n",
      "working on HD 8000 out of 8941\n",
      "working on HD 8800 out of 8941\n",
      "all done checking HD and complement contiguity for all 8941 HDs\n"
     ]
    }
   ],
   "source": [
    "patchedUse, unpUse, HDvPop = [0.]*nUnits, [0.]*nUnits, [0.]*nHDs\n",
    "for t in popHDlist:\n",
    "    if homeU[t] not in HDunitList[t]:\n",
    "        print(\"WARNING - we lost home unit\",homeU[t],\"from HD\",t)\n",
    "    for u in HDunitList[t]:\n",
    "        patchedUse[u] += HDweight[t] * nDistricts       \n",
    "        HDvPop[t] += unitPop[u]\n",
    "    if hasSplitUnit[t] == 1:\n",
    "        unitUse[splitUnitNo[t]] -= (1. - splitUnitFrac[t]) * nDistricts * HDweight[t]\n",
    "        HDvPop[t]               -= (1. - splitUnitFrac[t]) * unitPop[splitUnitNo[t]]\n",
    "#    for u in unpatchedHDlist[t]:\n",
    "#        unpUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(patchedUse,bins=50, label=\"patched\",histtype=\"step\")\n",
    "#plt.hist(unpUse, bins=50, label=\"unpatched\",histtype=\"step\")\n",
    "plt.legend()\n",
    "plt.show()\n",
    "patchedAvg, patchedSD = getWeightedAvgAndSD(patchedUse,unitPop)\n",
    "#unpatchedAvg, unpatchedSD = getWeightedAvgAndSD(unpUse,unitPop)\n",
    "print(\" patched use avg\", r5(patchedAvg),\"and SD\",r5(patchedSD) )\n",
    "#print(\"unpatched, patched use avgs are\",r5(unpatchedAvg), r5(patchedAvg),\"and their SDs are\",r5(unpatchedSD), r5(patchedSD) )\n",
    "print(\"And here is the pop distro\")\n",
    "\n",
    "plt.hist([HDvPop[t] for t in popHDlist])\n",
    "plt.axvline(aDP, ls=\"--\",color=\"orange\")\n",
    "plt.axvline(minDistrictPop, ls=\"dotted\")\n",
    "plt.axvline(maxDistrictPop, ls=\"dotted\")\n",
    "plt.show()\n",
    "print(\"checking contiguity of final HDs\")\n",
    "for t in popHDlist:\n",
    "    if t%800 == 0:\n",
    "        print(\"working on HD\",t,\"out of\",nHDs)\n",
    "    unbroken, noEnclave, sList, eList = enclaveCheck(HDunitList[t], unitNbrs)  #these HDunitLists now appear to be sets\n",
    "    if not unbroken or not noEnclave:\n",
    "        print(\"uh-oh, HD\",t,\"has contiguity, complement-contiguity of\",unbroken, noEnclave)\n",
    "print(\"all done checking HD and complement contiguity for all\",nHDs,\"HDs\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "id": "92e9e7c1-c3a3-4039-a1d7-1dfe5d9a727b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "patched save in HDunitList format\n"
     ]
    }
   ],
   "source": [
    "print(\"patched save in HDunitList format\")\n",
    "tList = [t for t in range(nHDs)]\n",
    "outDF = pd.DataFrame( {\"vtd\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDunitList\":HDunitList,\n",
    "                      \"splitUnitNo\":splitUnitNo,\"splitUnitFrac\":splitUnitFrac,\n",
    "                       \"centroid x\":HDCPx, \"centroid y\":HDCPy, \"homeU\":homeU, \"homeC\":countyNo } )\n",
    "outname = STATE+str(int(nHDs))+\"_\"+str(nDistricts)+\"_5cityPatch04.csv\" \n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "id": "2f2b0f2e-20ed-4220-846e-4a0bf687d1d7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "now write the final vtd lists to a file.  In this version, we had no splits, so assign vtds here\n"
     ]
    }
   ],
   "source": [
    "print(\"now write the final vtd lists to a file.  In this version, we had no splits, so assign vtds here\")\n",
    "finalVTDlist = [list() for t in range(nHDs)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        finalVTDlist[t] += unitTractList[u]\n",
    "tList = [t for t in range(nHDs)]\n",
    "outDF = pd.DataFrame( {\"vtd\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDvtdList\":finalVTDlist,\n",
    "                      \"centroid x\":HDCPx, \"centroid y\":HDCPy,\"countyNo\":countyNo,\"splitUnitNo\":splitUnitNo} )\n",
    "outname = STATE+str(int(nHDs))+\"_\"+str(nDistricts)+\"_5cityVTDs_04.csv\"\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)  #muni-based complete 11-11-24"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "164189ee-30cf-4cb2-80a9-22195eff585c",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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